Home Berries Author of general systems theory. Task for independent research. Examples: articulations, muscle groups, ocean currents, suspension bridges, book bindings, fixing glaciers and snow layers in mountains, etc.

Berries

Author of general systems theory. Task for independent research. Examples: articulations, muscle groups, ocean currents, suspension bridges, book bindings, fixing glaciers and snow layers in mountains, etc.

1. Introduction to systems theory.

2. The concept and properties of the system.

3. Elements of classification of systems.

4. The concept of a systematic approach.

5. System analysis of transport systems.

General systems theory(systems theory) - a scientific and methodological concept of the study of objects that are systems. It is closely related to the systematic approach and is a specification of its principles and methods. The first version of the general systems theory was put forward by Ludwig von Bertalanffy. Its main idea is to recognize the isomorphism of the laws governing the functioning of system objects.

The subject of research within this theory is the study of:

various classes, types and types of systems;

basic principles and patterns of behavior of systems (for example, the bottleneck principle);

processes of functioning and development of systems (for example, equilibrium, evolution, adaptation, infraslow processes, transient processes).

Within the boundaries of systems theory, the characteristics of any complexly organized whole are considered through the prism of four fundamental determining factors:

system device;

its composition (subsystems, elements);

the current global state of system conditioning;

an environment within whose boundaries all its organizing processes are deployed.

In exceptional cases, in addition, in addition to the study of these factors (structure, composition, state, environment), large-scale studies of the organization of elements of the lower structural-hierarchical levels, that is, the system infrastructure, are acceptable.

General systems theory and other systems sciences

Von Bertalanffy himself believed that the following scientific disciplines have (somewhat) common goals or methods with systems theory:

Cybernetics is the science of general patterns management processes and information transfer in various systems, whether it be machines, living organisms or society.

Information theory is a section of applied mathematics that axiomatically defines the concept of information, its properties and establishes limiting relationships for data transmission systems.

Game theory that analyzes, within the framework of a special mathematical apparatus, the rational competition of two or more opposing forces in order to achieve maximum gain and minimum loss.

Decision theory that analyzes rational choices within human organizations.

Topology that includes non-metric areas such as network theory and graph theory.

Factor analysis, that is, procedures for identifying factors in multivariable phenomena in sociology and other scientific fields.

Figure 1.1 - Systemology structure

General systems theory in the narrow sense, attempting to derive from general definitions of the concept of "system" a number of concepts characteristic of organized wholes, such as interaction, sum, mechanization, centralization, competition, finality, etc., and applying them to specific phenomena .

Applied Systems Science

It is customary to single out a correlate of systems theory in various applied sciences, sometimes referred to as systems sciences, or systems science. In applied systems sciences, the following areas are distinguished:

Systems Engineering, that is, scientific planning, design, evaluation and construction of man-machine systems.

Operations research, i.e. scientific management existing systems people, machines, materials, money, etc.

Engineering psychology (Eng. Human Engineering).

The field behavior theory of Kurt Lewin.

SMD-methodology, developed in the Moscow Methodological Circle by G. P. Shchedrovitsky, his students and colleagues.

Wolf Merlin's theory of integral individuality, based on Bertalanffy's theory.

Branch systems theories (specific knowledge about various types of systems) (examples: theory of mechanisms and machines, theory of reliability

System(from other Greek σύστημα - a whole made up of parts; connection) - a set of elements that are in relationships and connections with each other, which forms a certain integrity, unity.

According to Bertrand Russell: "A set is a collection of various elements, conceived as a single whole"

System - a set of elements that are interconnected

and relationships with each other, and forming a certain unity

property, integrity.

The property of the system is determined not only and by several elements

Comrade of its constituents how much the nature of the relationship between them.

Systems are characterized by an interconnection with the environment, in relation to

to which the system shows its integrity. To ensure

Integrity requires that the system has clear boundaries.

Systems are characterized by a hierarchical structure, i.e. each

element of the system is in turn a system, as well as any

the system is an element of the system more high level.

Element- the limit of the division of the system in terms of the aspect of consideration, the solution of a specific problem, the goal.

Connection– restriction of the degree of freedom of elements. They are characterized by direction (directed, non-directional), strength (strong, weak), character (subordination, generation, equal, control).

Structure reflects certain relationships, the relative position of the components of the system, its device (structure).

Concepts characterizing the functioning and development of the system:

A state is an instant photograph, a "slice" of the system, a stop in its development.

Behavior is a way to move from one state to another. (p. 30)

Equilibrium is the ability of a system in the absence of external perturbing influences (or under constant influences) to maintain its state for an arbitrarily long time.

Stability is the ability of a system to return to a state of equilibrium after it has been brought out by external (internal if there are active elements in the system) disturbing influences.

Development is a process aimed at changing material and spiritual objects in order to improve them.

Under development usually understand:

increasing the complexity of the system;

improvement of adaptability to external conditions (for example, the development of the organism);

increase in the scale of the phenomenon (for example, the development bad habit, natural disaster);

quantitative growth of the economy and qualitative improvement of its structure;

social progress.

Iskander Khabibrakhmanov wrote material on the theory of systems, the principles of behavior in them, relationships and examples of self-organization for the “Games Market” column.

We live in complex world and we do not always understand what is happening around. We see people who become successful without deserving it and those who are really worthy of success, but remain in obscurity. We are not sure about tomorrow we are closing more and more.

To explain things we don't understand, we invented shamans and fortune-tellers, legends and myths, universities, schools and online courses, but it didn't seem to help. When we were in school, we were shown the picture below and asked what would happen if we pulled a string.

Over time, most of us have learned to give the correct answer to this question. However, then we went out into the open world, and our tasks began to look like this:

This led to frustration and apathy. We have become like the wise men in the parable of the elephant, each of whom sees only a small part of the picture and cannot draw a correct conclusion about the object. Each of us has our own misunderstanding of the world, it is difficult for us to communicate it with each other, and this makes us even more lonely.

The fact is that we live in the age of a double paradigm shift. On the one hand, we are moving away from the mechanistic paradigm of society inherited from the industrial age. We understand that inputs, outputs and capacities do not explain the diversity of the world around us, and often it is much more influenced by the socio-cultural aspects of society.

On the other hand, a huge amount of information and globalization lead to the fact that instead of an analytical analysis of independent quantities, we must study interdependent objects, indivisible into separate components.

It seems that our survival depends on the ability to work with these paradigms, and for this we need a tool, just as we once needed tools for hunting and tilling the land.

One such tool is systems theory. Below there will be examples from systems theory and its general provisions, there will be more questions than answers and, hopefully, there will be some inspiration to learn more about it.

Systems theory

Systems theory is a fairly young science at the junction of a large number of fundamental and applied sciences. This is a kind of biology from mathematics, which deals with the description and explanation of the behavior of certain systems and the commonality between this behavior.

There are many definitions of the concept of a system, here is one of them. System - a set of elements that are in relationships, which forms a certain integrity of structure, function and processes.

Depending on the objectives of the research, the systems are classified:

by the presence of interaction with the outside world - open and closed;
by the number of elements and the complexity of the interaction between them - simple and complex;
if possible, observations of the entire system - small and large;
by the presence of an element of randomness - deterministic and non-deterministic;
by the presence of goals in the system - casual and purposeful;
according to the level of organization - diffuse (random walks), organized (the presence of a structure) and adaptive (the structure adapts to external changes).

Also, systems have special states, the study of which gives an understanding of the behavior of the system.

sustainable focus. With small deviations, the system returns to its original state again. An example is a pendulum.
Unstable focus. A small deviation brings the system out of equilibrium. An example is a cone placed with a point on a table.
Cycle. Some states of the system are cyclically repeated. An example is the history of different countries.
Complex behavior. The behavior of the system has a structure, but it is so complex that it is not possible to predict the future state of the system. An example is stock prices on the stock exchange.
Chaos. The system is completely chaotic, there is no structure in its behavior.

Often when working with systems, we want to make them better. Therefore, we need to ask ourselves the question in what special state we want to bring it. Ideally, if the new state of interest to us is a stable focus, then we can be sure that if we achieve success, then it will not disappear the next day.

Complex systems

We are increasingly seeing complex systems around us. Here I did not find sounding terms in Russian, so I have to speak in English. There are two fundamentally different concepts of complexity.

The first (complicatedness) - means some complexity of the device, which is applied to fancy mechanisms. This kind of complexity often makes the system unstable to the slightest changes in the environment. So, if one of the machines stops at the plant, it can disable the entire process.

The second (complexity) - means the complexity of behavior, for example, biological and economic systems(or their emulations). On the contrary, this behavior persists even with some changes in the environment or the state of the system itself. So, when a major player leaves the market, the players will share his share less among themselves, and the situation will stabilize.

Often complex systems have properties that can lead the uninitiated into apathy, and make working with them difficult and intuitive. These properties are:

simple rules for complex behavior,
butterfly effect or deterministic chaos,
emergence.

Simple rules for complex behavior

We are used to the fact that if something exhibits complex behavior, then it is most likely complex internally. Therefore, we see patterns in random events and we try to explain things that are incomprehensible to us by the machinations of evil forces.

However, this is not always the case. A classic example of a simple internal structure and complex external behavior is the game of life. It consists of a few simple rules:

the universe is a checkered plane, there is an initial arrangement of living cells.
at the next moment of time, a living cell lives if it has two or three neighbors;
otherwise it dies of loneliness or overpopulation;
in an empty cell, next to which there are exactly three living cells, life is born.

In general, writing a program that will implement these rules will require five to six lines of code.

Wherein this system can produce quite complex and beautiful patterns of behavior, so without seeing the rules themselves it is difficult to guess them. And it's certainly hard to believe that this is implemented in a few lines of code. Perhaps the real world is also built on a few simple laws that we have not yet deduced, and the entire boundless variety is generated by this set of axioms.

Butterfly Effect

In 1814, Pierre-Simon Laplace proposed a thought experiment that sentient being, capable of perceiving the position and speed of every particle of the universe and knowing all the laws of the world. The question was the theoretical ability of such a being to predict the future of the universe.

This experiment caused a lot of controversy in scientific circles. Scientists, inspired by progress in computational mathematics, tended to answer yes to this question.

Yes, we know that the principle of quantum uncertainty excludes the existence of such a demon even in theory, and predicting the position of all particles in the world is fundamentally impossible. But is it possible in simpler deterministic systems?

Indeed, if we know the state of the system and the rules by which they change, what prevents us from calculating the next state? Our the only problem there may be a limited amount of memory (we can store numbers with limited precision), but all calculations in the world work this way, so this should not be a problem.

Not really.

In 1960, Edward Lorenz created a simplified weather model, consisting of several parameters (temperature, wind speed, pressure) and the laws by which the state at the next time is obtained from the current state, representing a set of differential equations.

dt = 0.001

x0 = 3.051522

y0 = 1.582542

z0 = 15.623880

xn+1 = xn + a(-xn + yn)dt

yn+1 = yn + (bxn - yn - znxn)dt

zn+1 = zn + (-czn + xnyn)dt

He calculated the values of the parameters, displayed them on the monitor and built graphs. It turned out something like this (graph for one variable):

After that, Lorentz decided to rebuild the graph, taking some intermediate point. It is logical that the graph would have turned out exactly the same, since the initial state and the transition rules have not changed in any way. However, when he did, something unexpected happened. In the graph below, the blue line represents the new set of parameters.

That is, at first both graphs go very close, there are almost no differences, but then the new trajectory moves further and further away from the old one, starting to behave differently.

As it turned out, the reason for the paradox lay in the fact that in the computer's memory all data was stored with an accuracy of up to the sixth decimal place, and was displayed with an accuracy of up to the third. That is, a microscopic change in the parameter led to a huge difference in the trajectories of the system.

It was the first deterministic system to have this property. Edward Lorenz gave it the name The Butterfly Effect.

This example shows us that sometimes events that seem unimportant to us end up having a huge impact on outcomes. The behavior of such systems is impossible to predict, but they are not chaotic in the truest sense of the word, because they are deterministic.

Moreover, the trajectories of this system have a structure. In three-dimensional space, the set of all trajectories looks like this:

What is symbolic, it looks like a butterfly.

emergence

Thomas Schelling, an American economist, looked at maps of the distribution of racial classes in various American cities, and observed the following pattern:

This is a map of Chicago and here different colors the places of residence of people of different nationalities are depicted. That is, in Chicago, as in other cities in America, there is a fairly strong racial segregation.

What conclusions can we draw from this? The first thing that comes to mind is: people are intolerant, people do not accept and do not want to live with people who are different from them. But is it?

Thomas Schelling proposed the following model. Imagine a city in the form of a checkered square, people of two colors (red and blue) live in the cells.

Then almost every person from this city has 8 neighbors. It looks something like this:

Moreover, if a person has less than 25% of neighbors of the same color, then he randomly moves to another cell. And so it continues until each resident is satisfied with his position. The inhabitants of this city cannot be called intolerant at all, because they only need 25% of people like them. In our world, they would be called saints, a real example of tolerance.

However, if we start the process of moving, then from the random location of the inhabitants above, we will get the following picture:

That is, we get a racially segregated city. If, instead of 25%, each resident wants at least half of the neighbors like him, then we will get almost complete segregation.

Wherein this model does not take into account such things as the presence of local temples, shops with national utensils, and so on, which also increase segregation.

We are accustomed to explaining the properties of a system by the properties of its elements and vice versa. However, for complex systems, this often leads us to incorrect conclusions, because, as we have seen, the behavior of the system at the micro and macro levels can be opposite. Therefore, often going down to the micro level, we try to do the best, but it turns out as always.

This property of a system, when the whole cannot be explained by the sum of its elements, is called emergence.

Self-organization and adaptive systems

Perhaps the most interesting subclass of complex systems are adaptive systems, or systems capable of self-organization.

Self-organization means that the system changes its behavior and state, depending on changes in outside world, it adapts to changes, constantly transforming itself. Such systems everywhere, almost any socio-economic or biological, just like the community of any product, are examples of adaptive systems.

Here is a video of the puppies.

At first, the system is in chaos, but when an external stimulus is added, it becomes more orderly and quite nice behavior appears.

Ant Swarm Behavior

The foraging behavior of an ant swarm is a perfect example of an adaptive system built around simple rules. When looking for food, each ant wanders randomly until it finds food. Having found food, the insect returns home, marking the path it has traveled with pheromones.

At the same time, the probability of choosing a direction when wandering is proportional to the amount of pheromone (smell strength) on this path, and over time, the pheromone evaporates.

The efficiency of the ant swarm is so high that a similar algorithm is used to find the optimal path in graphs in real time.

At the same time, the behavior of the system is described by simple rules, each of which is critical. So the randomness of wandering allows you to find new food sources, and the evaporability of the pheromone and the attractiveness of the path, proportional to the strength of the smell, allows you to optimize the length of the route (by shortcut, the pheromone will evaporate more slowly as new ants add their pheromone).

Adaptive behavior is always somewhere between chaos and order. If there is too much chaos, then the system reacts to any, even insignificant, change and cannot adapt. If there is too little chaos, then stagnation is observed in the behavior of the system.

I have observed this phenomenon in many teams where the presence of clear job descriptions and rigidly regulated processes made the team toothless, and any noise outside unsettled it. On the other hand, the lack of processes led to the fact that the team acted unconsciously, did not accumulate knowledge, and therefore all its unsynchronized efforts did not lead to a result. Therefore, the construction of such a system, and this is the task of most professionals in any dynamic field, is a kind of art.

In order for the system to be capable of adaptive behavior, it is necessary (but not sufficient):

openness. A closed system cannot adapt by definition because it knows nothing about the outside world.
Presence of positive and negative feedbacks. Negative feedbacks keep the system in a favorable state as they reduce the response to outside noise. However, adaptation is impossible without positive feedbacks that help the system to move into a new best condition. When it comes to organizations, processes are responsible for negative feedbacks, while new projects are responsible for positive feedbacks.
Variety of elements and relationships between them. Empirically, increasing the variety of elements and the number of connections increases the amount of chaos in the system, so any adaptive system must have the necessary amount of both. Diversity also allows for a smoother response to change.

Finally, I would like to give an example of a model that emphasizes the need for a variety of elements.

It is very important for a bee colony to maintain a constant temperature in the hive. Moreover, if the temperature of the hive falls below the desired for a given bee, she begins to flap her wings to warm the hive. Bees have no coordination and the desired temperature is built into the bee's DNA.

If all the bees have the same desired temperature, then when it drops below, all the bees will begin to flap their wings at the same time, quickly warm the hive, and then it will also quickly cool down. The temperature graph will look like this:

And here is another graph where the desired temperature for each bee is randomly generated.

The temperature of the hive is kept at a constant level, because the bees are connected to the heating of the hive in turn, starting from the most "freezing".

That's all, finally, I want to repeat some of the ideas that were discussed above:

Sometimes things are not quite what they seem.
Negative feedback helps you stay put, positive feedback helps you move forward.
Sometimes, to make it better you need to add chaos.
Sometimes simple rules are enough for complex behavior.
Appreciate variety, even if you're not a bee.

Lecture 1: Basic concepts of systems theory

The terms systems theory and system analysis, despite the period of more than 25 years of their use, still have not found a generally accepted, standard interpretation.

The reason for this fact lies in the dynamism of processes in the field of human activity and in the fundamental possibility of using a systematic approach in almost any task solved by a person.

General systems theory (GTS) is a scientific discipline that studies the most fundamental concepts and aspects of systems. It studies various phenomena, abstracting from their specific nature and based only on the formal relationships between the various factors that make them up and on the nature of their change under the influence of external conditions, while the results of all observations are explained only by the interaction of their components, for example, the nature of their organization and functioning, and not by directly addressing the nature of the mechanisms involved (whether physical, biological, ecological, sociological, or conceptual)

For GTS, the object of study is not a "physical reality", but a "system", i.e. abstract formal relationship between the main features and properties.

With a systematic approach, the object of study is presented as a system. The very concept of a system can be related to one of the methodological concepts, since the consideration of an object is investigated as a system or the refusal of such consideration depends on the research task and the researcher himself.

There are many definitions of a system.

A system is a complex of elements that interact.
A system is a set of objects together with the relations of these objects.
System - a set of elements that are in relationships or connections with each other, forming integrity or organic unity (explanatory dictionary)

The terms "relationship" and "interaction" are used in the broadest sense, including the whole set of related concepts such as restriction, structure, organizational connection, connection, dependence, etc.

Thus, the system S is an ordered pair S=(A, R), where A is a set of elements; R is the set of relationships between A.

A system is a complete, integral set of elements (components) interconnected and interacting with each other so that the function of the system can be realized.

The study of an object as a system involves the use of a number of representation systems (categories), among which the main ones are:

Structural representation is associated with the selection of the elements of the system and the links between them.
Functional representation of systems - the allocation of a set of functions (purposeful actions) of the system and its components aimed at achieving a specific goal.
Macroscopic representation is the understanding of the system as an indivisible whole interacting with the external environment.
The microscopic representation is based on the consideration of the system as a set of interrelated elements. It involves the disclosure of the structure of the system.
The hierarchical representation is based on the concept of a subsystem, obtained by decomposing (decomposing) a system that has system properties that should be distinguished from its element, which is indivisible into smaller parts (from the point of view of the problem being solved). The system can be represented as a set of subsystems of various levels, constituting a system hierarchy, which is closed from below only by elements.
The procedural representation assumes the understanding of a system object as a dynamic object, characterized by a sequence of its states in time.

Let us consider the definitions of other concepts closely related to the system and its characteristics.

An object.

The object of knowledge is a part of the real world, which stands out and is perceived as a whole for a long time. The object can be material and abstract, natural and artificial. In reality, an object has an infinite set of properties of various nature. In practice, in the process of cognition, interaction is carried out with a limited set of properties that lie within the limits of the possibility of their perception and necessity for the purpose of cognition. Therefore, the system as an image of an object is defined on a finite set of properties selected for observation.

External environment.

The concept of "system" arises there and then, where and when we materially or speculatively draw a closed boundary between an unlimited or some limited set of elements. Those elements with their respective mutual conditioning that fall inside form a system.

Those elements that remained outside the boundary form a set, called in systems theory "system environment" or simply "environment", or "external environment".

It follows from these considerations that it is unthinkable to consider a system without its external environment. The system forms and manifests its properties in the process of interaction with the environment, while being the leading component of this impact.

Depending on the impact on the environment and the nature of interaction with other systems, the functions of systems can be arranged in ascending rank as follows:

passive existence;
material for other systems;
maintenance of higher order systems;
opposition to other systems (survival);
absorption of other systems (expansion);
transformation of other systems and environments (active role).

Any system can be considered, on the one hand, as a subsystem of a higher order (supersystem), and on the other hand, as a supersystem of a system of a lower order (subsystem). For example, the system "production shop" is included as a subsystem in a system of a higher rank - "firm". In turn, the "firm" supersystem can be a "corporation" subsystem.

Usually, more or less independent parts of systems appear as subsystems, distinguished according to certain characteristics, possessing relative independence, a certain degree of freedom.

Component- any part of the system that enters into certain relations with other parts (subsystems, elements).

element system is a part of a system with uniquely defined properties that perform certain functions and are not subject to further division within the framework of the problem being solved (from the point of view of the researcher).

The concepts of element, subsystem, system are mutually transformable, the system can be considered as an element of a system of a higher order (metasystem), and an element, in in-depth analysis, as a system. The fact that any subsystem is simultaneously and relatively independent system leads to 2 aspects of the study of systems: at the macro- and micro-levels.

When studying at the macro level, the main attention is paid to the interaction of the system with the external environment. Moreover, higher-level systems can be considered as part of the external environment. With this approach, the main factors are the target function of the system (goal), the conditions for its functioning. At the same time, the elements of the system are studied from the point of view of their organization into a single whole, the impact on the functions of the system as a whole.

At the micro level, the main internal characteristics systems, the nature of the interaction of elements among themselves, their properties and conditions of functioning.

Both components are combined to study the system.

System structure.

The structure of the system is understood as a stable set of relations that remains unchanged for a long time, according to at least during the observation interval. The structure of the system is ahead of a certain level of complexity in terms of the composition of relations on the set of elements of the system, or equivalently, the level of diversity of the manifestations of the object.

Connections- these are elements that carry out direct interaction between elements (or subsystems) of the system, as well as with elements and subsystems of the environment.

Communication is one of the fundamental concepts in the systems approach. The system as a whole exists precisely due to the presence of connections between its elements, i.e., in other words, the connections express the laws of the system's functioning. Relations are distinguished by the nature of the relationship as direct and reverse, and by the type of manifestation (description) as deterministic and probabilistic.

Direct connections are intended for a given functional transfer of matter, energy, information or their combinations - from one element to another in the direction of the main process.

Feedback, mainly perform informing functions, reflecting a change in the state of the system as a result of a control action on it. The discovery of the feedback principle was an outstanding event in the development of technology and had extremely important consequences. The processes of management, adaptation, self-regulation, self-organization, development are impossible without the use of feedback.

Rice. — Feedback example

With the help of feedback, the signal (information) from the output of the system (control object) is transmitted to the control body. Here, this signal, containing information about the work performed by the control object, is compared with a signal that specifies the content and amount of work (for example, a plan). In the event of a discrepancy between the actual and planned state of work, measures are taken to eliminate it.

The main feedback functions are:

counteracting what the system itself does when it goes beyond the established limits (for example, responding to quality degradation);
compensation of disturbances and maintenance of a state of stable equilibrium of the system (for example, equipment malfunctions);
synthesizing external and internal disturbances that seek to bring the system out of a state of stable equilibrium, reducing these disturbances to deviations of one or more controlled variables (for example, the development of control commands for the simultaneous appearance of a new competitor and a decrease in the quality of products);
development of control actions on the control object according to a poorly formalized law. For example, the establishment of a higher price for energy carriers causes complex changes in the activities of various organizations, changes the final results of their functioning, requires changes in the production and economic process through impacts that cannot be described using analytical expressions.

Violation of feedback in socio-economic systems for various reasons leads to serious consequences. Separate local systems lose the ability to evolve and finely perceive emerging new trends, long-term development and scientifically based forecasting of their activities for a long period of time, effective adaptation to constantly changing environmental conditions.

A feature of socio-economic systems is the fact that it is not always possible to clearly express the feedback, which in them, as a rule, is long, passes through a number of intermediate links, and it is difficult to see them clearly. The controlled variables themselves often do not lend themselves to a clear definition, and it is difficult to establish many restrictions on the parameters of the controlled variables. The real reasons for the controlled variables to go beyond the established limits are also not always known.

A deterministic (hard) connection, as a rule, unambiguously determines the cause and effect, gives a clearly defined formula for the interaction of elements. A probabilistic (flexible) connection defines an implicit, indirect relationship between the elements of the system. Probability theory offers a mathematical apparatus for the study of these relationships, called "correlation dependencies."

Criteria- signs by which the assessment of the compliance of the functioning of the system with the desired result (goal) is carried out under given restrictions.

System efficiency- the ratio between the given (target) indicator of the result of the functioning of the system and actually implemented.

Functioning of any arbitrarily chosen system consists in processing the input (known) parameters and known parameters of the environmental impact into the values of the output (unknown) parameters, taking into account feedback factors.

Rice. — System operation

entrance- everything that changes during the course of the process (functioning) of the system.

Exit is the result of the final state of the process.

CPU— transfer of input to output.

The system communicates with the environment in the following way.

The input of a given system is at the same time the output of the previous one, and the output of this system is the input of the next one. Thus, the input and output are located on the boundary of the system and simultaneously perform the functions of the input and output of the previous and subsequent systems.

System management is associated with the concepts of direct and feedback, restrictions.

Feedback- designed to perform the following operations:

comparison of input data with output results with the identification of their qualitative and quantitative differences;
assessment of the content and meaning of the difference;
working out a solution arising from the difference;
impact on input.

Limitation- provides a correspondence between the output of the system and the requirement for it, as for the input to the subsequent system - the consumer. If the specified requirement is not met, the constraint does not allow it to pass through itself. The restriction, therefore, plays the role of coordinating the functioning of this system with the goals (needs) of the consumer.

The definition of the functioning of the system is associated with the concept of a “problem situation”, which occurs if there is a difference between the necessary (desired) output and the existing (real) input.

Problem is the difference between the existing system and the desired system. If there is no difference, then there is no problem.

Solving a problem means correcting an old system or designing a new, desirable one.

System status is the set of essential properties that the system possesses at any given time.

An Austrian biologist living in Canada and the United States, Ludwig von Bertalanffy, first put forward a number of ideas in 1937, which he later combined into one concept. He called it General Systems Theory. What is it? This is the scientific concept of studying various objects considered as a system.

The main idea of the proposed theory was that the laws governing system objects are unified, the same for different systems. In fairness, it must be said that the main ideas of L. Bertalanffy were laid down by various scientists, including the Russian philosopher, writer, politician, doctor, in his fundamental work "Tectology", written by him in 1912. A.A. Bogdanov actively participated in the revolution, however, in many respects he did not agree with V.I. Lenin. did not accept, but, nevertheless, continued to cooperate with the Bolsheviks, organizing the first Institute of Blood Transfusion in what was then Russia and putting on a medical experiment. He died in 1928. Few people know even today that at the beginning of the twentieth century, the Russian physiologist V.M. Bekhterev, regardless of A.A. Bogdanov, described more than 20 universal laws in the field of psychological and social processes.

General systems theory studies different kinds, the structure of systems, the processes of their functioning and development, the organization of components of structural-hierarchical levels, and much more. L. Bertalanffy also studied the so-called open systems exchanging free energy, matter and information with the environment.

General systems theory currently explores such system-wide regularities and principles as, for example, the hypothesis of semiotic feedback, organizational continuity, compatibility, complementary relationships, the law of necessary diversity, hierarchical compensations, the principle of monocentrism, the least relative resistances, the principle of external complement, the theorem of recursive structures, the law of divergence and others.

The current state of the systems sciences owes much to L. Bertalanffy. General systems theory is in many ways similar in terms of goals or research methods to cybernetics - the science of the general laws of the process of control and transmission of information in different systems (mechanical, biological or social); information theory - a branch of mathematics that defines the concept of information, its laws and properties; game theory, which analyzes with the help of mathematics the competition of two or more opposing forces in order to obtain the greatest gain and the least loss; decision theory, which analyzes rational choices among various alternatives; factor analysis, which uses the procedure for extracting factors in phenomena with many variables.

Today, the general theory of systems is receiving a powerful impetus for its development in synergetics. I. Prigogine and G. Haken investigate non-equilibrium systems, dissipative structures and entropy in open systems Oh. In addition, such applied scientific disciplines as system engineering, the science of system planning, design, evaluation and construction of systems of the “man-machine” type, emerged from the theory of L. Bertalanffy; engineering psychology; field behavior theory operations research - the science of managing the components of economic systems (people, machines, materials, finance, etc.); SMD methodology, which was developed by G.P. Shchedrovitsky, his staff and students; the theory of integral individuality by V. Merlin, which was based largely on the general theory of Bertalanffy systems discussed above.

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MINISTRY OF EDUCATION AND SCIENCE OF RUSSIA

Federal State Autonomous Educational

institution of higher professional education

"SOUTH FEDERAL UNIVERSITY"

Faculty of Geology and Geography

Concepts of modern natural science

Part 3 General systems theory

Methodological development for independent work

for 2nd year students

specialty 100201 "Tourism »

I.F. Cherkashin

Rostov-on-Don 2011

1. The role and place of a systematic approach in natural science

Word "system" in Greek means "a whole made up of parts." These parts are called ""elements" The last word is the Latin equivalent of the Greek word "element" (fire, air, water, earth, see lecture No. 3), that is, "the beginning."

In the modern scientific understanding, "a system is a single whole, representing a set of interrelated elements." There are other definitions of "system". Thus, Russian science expert VN Sadovsky gives 34 definitions of the word "system". Therefore, due to the breadth of the concept of "system" of the generally accepted scientific definition what is the system yet. In fact, any natural object is a system: it consists of at least elementary particles.

PExamples systems:

1. The solar system is a collection of planets and other celestial bodies located in the sphere of attraction of the Sun.

The human body is a system of cells, organs, functional systems within the human body.

A computer is a set of parts (system unit, keyboard, display, processor, memory unit, etc.) that serve to perform complex logical and mathematical actions.

Educational Institute - an institution consisting of faculties, departments, teachers, students, premises, equipment, support staff and intended for the purposes of higher education.

5. Biogeocenosis - a system of plants, animals and microorganisms

together with the soil and climatic conditions of habitat.

Any system can be depicted using a drawing (diagram), reflecting the main elements and the relationships between them.

From the examples given, it can be seen that consistency as a concept wider than the framework of natural science, it refers both to nature (including wild), and to science and culture in general. The largest system is obviously the Universe.

In turn systems approach(not only within the framework of natural science) combines into a single whole system method and general systems theory.

"It is clear that the world is a single system, that is, a coherent whole." F. Engels

2. System methods

This method scientific knowledge has been known in its main features since ancient times. It arose simultaneously with science as a system of knowledge about the regularities of the studied phenomena and was known in ancient Greece in the era of antiquity. A systemic view of the world as a whole and its individual parts (i.e., a systemic concept) is found in Plato, the hero of whose work - Professor Timaeus - speaks of the world body as a living organism. Viewed the world the same way Diogenes. Pythagoras considered the world to be a harmonic system of numbers and their relations. But Aristotle especially developed the system method in his works. He believed that

"Elements are understood as the limiting parts into which bodies are divisible, but which are no longer divisible into others that differ from them in appearance."

Aristotle can be considered the creator systemologistandand-- a science that studies phenomena from a systemic point of view. As is known, he systematized the achievements of other Greek scientists to the greatest extent, and the system of the world Plato - Eudoxus(homocentric spheres) brought to the highest perfection.

In later epochs, systemic views (concepts) in natural science did not disappear, but were passed on from generation to generation of scientists. French encyclopedist Paul Holbach (1723-1789). In 1770, in his work "The System of Nature", he detailed the first physical picture of the world (mechanical), which was developed by Newton and Laplace.

Thus, the systematic method in natural science turned out to be very productive, although not absolute, suitable for all occasions.

And the system method, like any other, has certain errors (methodological errors). The system method is often referred to as system analysis.

3 . General systems theory

Unlike system method that arose with the advent of science, general systems theory(OTS) is a product modern era. At the same time, OTS should be differentiated from systemology. The latter can be considered a section methodology-- sciences of methods, while OTS is a scientific result (achievement) system analysis, i.e. scientific theory, which embodied the results of previous systematic studies.

The concept of a system-wide approach was formulated by an Austrian biologist Ludwig von Bertalanffy in the 20s XX century, although he had predecessors, including a domestic naturalist, economist, philosopher, managerial scientist Alexander Alexandrovich Bogdanov (1873-- 1928).

In 1927, Bertalanffy published the book "Organismic Concept", in which he substantiated the need to study not only individual organs and particular systems of a biological organism (for example, the nervous system, muscle, bone, etc.), but also the whole organism. However, this was not OTS yet. The GTS concept, referring to systems of any nature: biological, engineering, social, etc., mainly complex, was approved by Bertalanffy, then an assistant professor University of Vienna, in his scientific lectures delivered at the University of Chicago (USA) in 1938. The text of the lectures, initially coolly accepted, was later published in the USA in 1945 and 1949.

Bertalanffy's guiding idea was that complex systems of various nature, having completely different composition and structure(e.g. biological organisms, industries, cities, airports, etc.), are functioning according to general laws. And therefore knowledge gained in the study of some systems can be transferred to the study of other systems of a completely different nature. Thus, Bertalanffy in his research took advantage of by analogy.

This achievement had important consequences for the natural and human sciences. First of all, Bertalanffy was able to help biology, dealing with systems of the most complex nature. He paved the way for the use in the study of living methods and results of physics, chemistry, mathematics (especially mathematical modeling), and in the future - geology and cosmology. Such achievements have gone far beyond biology and formed a general scientific systems approach.

The systematic approach first established itself in biology, then moved into its applied part - medicine (first into psychiatry, then completely other sections), eventually settled in military affairs, astronautics, linguistics, production management, cultural studies, history and, of course, in all branches of natural science. Thus, by the mid-50s of the XX century. the systematic approach in science became universal, and in the USSR the productive development of scientific and economic applications of this approach began in the 1960s. At present, systems research is successfully developing all over the world, although the euphoria from the supposedly unlimited possibilities of GTS has already passed.

To get acquainted with the main provisions of the GTS, it is necessary to introduce the basic concepts related to it. In addition to the given concept of SYSTEM, the following concepts (definitions) are used in the GTS:

1) ELEMENT - an integral part of the system, which, under the conditions of consideration, is considered indivisible. The elements may be the same or different.

Examples: atoms in a molecule; students in a group; planets, comets, meteors in the solar system; axioms, postulates, theorems, equations, lemmas in mathematics; and etc.

2) SUBSYSTEM - an integral part of the system, which, under the conditions of consideration, is considered to be divisible into elements, in relation to which it acts as a system.

Examples: the cardiovascular system in the body; mission control center at the cosmodrome; mining industry; student group, etc.

There can be many subsystems in the system, they can be either "nested" one into another, or exist separately. But in both such cases, the relationship between elements, subsystems and the system always has the character of subordination, i.e., the "lower" (elements) are subordinate to the "higher" (subsystem), which in turn is subordinate to the "higher" (system). This introduces the concept of the level of organization. The sequence of levels of subordination in the system is called the "hierarchy" in Greek. "sacred authority"). The latter term entered the OTS in the 20th century. from church-Christian terminology that existed as early as the 5th century. n. e.

3) ENVIRONMENT (external, surrounding) - the environment of the system (usually real), in which it resides and with which it interacts to one degree or another.

Since the environment surrounds the system, its name is often used in combination with the words "environment", "external".

Examples: intercellular fluid surrounding biological cells; vacuum in relation to elementary particles; solvent versus solute; production shop in relation to workers; and etc.

The collective term is often used internal environment. It refers to the environment located inside the system (subsystem). For example, blood is one of the internal environments of the body, but it is also external environment for blood elements: erythrocytes, leukocytes, platelets, etc. Thus, fundamental difference between external and internal environment ami no, it all depends on the conditions of consideration. The already mentioned A. A. Bogdanov in his work "The General Organizational Science" (1927) rightly noted:

"Pathogenic bacteria multiply inside the body, but functionally they are an external environment for it."

Moreover, there is also no fundamental difference between the system and the environment: everything again depends on the reference point. The environment can be considered as a system, then former system becomes the environment. For example, volcanic lava in the nozzle of a volcano can be considered as a system, then the nozzle will be a medium. If lava is considered a medium, then the nozzle becomes a system.

The relationship of the system, subsystem, external and internal environments and elements are schematically shown in Fig. 1, where, for simplicity, the elements are shown only within one subsystem out of six;

Rice. 1. Scheme of relationships in the system

4) COMPOSITION - a set of elements of the system. It can be: a) quality when only the qualitative certainty of the elements is indicated; for example: goalkeeper, defenders, midfielders, forwards in a football team; sodium and chlorine ions in a salt crystal; b) quantitative, when not only the qualitative certainty of the elements is specified, but also their quantitative ratio; for example: in a physiological solution of 0.9% dissolved sodium chloride, 99.1% - water; in gold of the 958th test - 95.8% gold, 2.0% silver and 2.2% copper;

5) STRUCTURE - the relative position of elements in the system, i.e. in fact, the internal structure of the system, in contrast to the form - the external structure. Examples: the structure of an atom, a molecule, the cells of an organism, the structure of the solar system, a device, etc.

To establish the structure of objects is used structural analysis. It can be destructive (biological tissue slicing for microscopy, thin sections of geological samples, etc.) or non-destructive (chest X-ray, ultrasound "shine" of railway rails to detect hidden cracks, etc.). The revealed structure can be registered (for example, on photographic film) or described schematically (Fig. 2).

Rice. 2. Different ways of representing the structure of the water molecule

Structure together with composition system defines it basic properties(physical, chemical, biological). With the same composition of different systems, their structures may differ, and this entails a change in properties. For example, the same carbon atoms C included in the molecular structure of graphite or diamond give completely different properties of these substances (color, strength, etc.);

6) STATE - an integral characteristic of manifestation in this moment time properties of the system, depending on all the features of its structure and composition. Examples: the state of solar activity on a particular day; the state of the gas in a certain volume at a given time; pre-start psychological state of the athlete; the morbid condition of a person during an epidemic; and others. To describe the state, there is a set of state characteristics and state parameters. The characteristics of the state reflect, as it were, its character at the moment. These characteristics include:

equilibrium and non-equilibrium state;

stability and instability of equilibrium;

static and dynamic balance;

initial, intermediate, final and current state, etc.

The state parameters include certain quantities, the numerical values of which are currently sufficient to unambiguously determine the integral state of the system. For example, for 1 mole of an ideal gas, its state is uniquely given using the Clapeyron equation:

For this equation, the state parameters of the system are p, V and T. Of these, only two (any) are independent, the third parameter is uniquely established from the above equation. The minimum number of parameters sufficient to describe the state of the system is called the number of degrees of freedom of the system. 1 mole of an ideal gas (as, indeed, a constant mass of a gas of a certain chemical composition) has two degrees of freedom;

7) PROCESS -- a change in the state of the system over time, sometimes called a system process. Examples: the process of recovering a patient, a chemical reaction (a process with the transformation of substances); physical process (without the transformation of substances: evaporation, melting, etc.); intrastellar processes; political processes; etc.

The process is one of the forms of matter movement, therefore, this characteristic of the system will be given in more detail in lecture No. 9.

4. Classificationsystems

Systems are classified in a variety of ways, using various criteria. Some classes of systems are independent of each other, others are interconnected. Consider the classification features used in the division of systems. one) Composition systems are divided into:

¦ material-- representing collections of material objects:

Examples; animal world, vegetation, mankind,

transport, libraries, etc.

These systems can be divided into natural (natural) and artificial (man-made). Material systems are also called physical, real, real;

¦ ideal are products of human thought. Examples: number systems, theater systems, systems of education and upbringing, scientific theories, religious teachings, etc. These systems are also called abstract, symbolic.

2) By behavior in time, the systems are divided into:

¦ static- such systems, the state of which practically does not change over time.

Examples: deserts, mountains, solar system, gas in a closed vessel, church canons, etc.

These systems are also called static.

¦ dynamic- systems, the state of which noticeably changes with time.

Examples: weather, traffic situation, programming languages, piece of music (performed), chess game, chemical reaction, etc.

These systems are also called dynamic.

A clear boundary between static and dynamic systems cannot be drawn; everything depends on the conditions of consideration and the time scale.

In turn, dynamic systems are divided into:

¦ deterministic, for which their future states can be accurately predicted, are derived from previous states.

Examples: Solar eclipses (positions of the Earth, Moon and Sun), change of seasons, traffic control systems using traffic lights, factory machine operation, etc.

¦ vprobabilistic, for which their future states cannot be accurately predicted, but can only be predicted probabilistically.

Examples: Brownian motion (coordinates of particles undergoing ~1021 molecular impacts per second), weather a week later, scores of a large proportion of students in exams, victories in sports competitions, etc.

Probabilistic systems are also called stochastic. Usually biological systems are probabilistic.

¦ ddeterministically chaotic- this is a relatively new type of systems in science, it is not intermediate (boundary) for the first two. This type of systems is associated with the mutual transition of chaos and order (i.e., determinism and stochasticity) and will be discussed in detail in lecture No. 13. 3) By interaction with the environment, systems are divided into: their medium is matter and field, more precisely, such an exchange can be neglected under the conditions of consideration.

Examples: conservative mechanical systems (conserving mass and energy), tea in a thermos, stable galaxies in the vacuum of space, underground oil storage facilities, etc.

¦ open- in contrast to the first, they exchange matter and field with the environment.

Examples: all living organisms, seas and oceans, soils, the Sun, communication systems, manufacturing plants, public associations, etc.

Closed systems are also called closed, or isolated, and open - open, or not isolated. In addition, according to modern refined scientific concepts of natural science as exchange agents between the system and the environment should be indicated not the substance and the field, but matter, energy and information.

Finally, it should be noted that there are no purely closed systems in nature and society, at least for dialectical reasons. Therefore, closed systems are an example of a speculative scientific model.

¦ simple - systems consisting of a relatively small number of elements and simple relationships between them, usually these are technical systems.

Examples: watch, camera, iron, furniture, tools, broom, book, etc.;

¦complex - systems consisting of a large number of elements and complex relationships between them; such systems occupy a central place in systemology and OTS.

Examples: all biological systems, from cells to communities of organisms, industrial associations, states, nations, galaxies, complex technical systems: computers, combat missiles, nuclear power plants, etc.

Complex systems are also referred to as "large" or "very large" systems. In the vast majority of cases, they are both probabilistic systems (see above), but sometimes there are also deterministic, highly organized systems: an innate defensive reflex in a cat, the position of planets, asteroids solar system, military parade, etc.

¦ Targeted- systems that are able to model and predict the situation and choose the way of behavior (state changes): due to the perception and recognition of external influences, the ability to analyze and compare it with their own capabilities and choose one or another behavior option to achieve the goal.

Examples: lunar rover, rover, robotic arms, swarms of bees, herds of animals, schools of fish, homing missiles, flocks of migratory birds, etc.

Purposeful systems have a certain set of "knowledge" about themselves and about the environment, in other words, they have a thesaurus (from the Greek "treasury") - a store of information about reality inherent in an individual (or a community of individuals), with the ability to perceive new information and accumulate experience. Purposeful systems usually have the ability, in philosophical language, to anticipate the reflection of reality. For example, trees accumulate moisture in anticipation of a drought, birds build nests even before the appearance of future chicks, etc.

¦ Unfocused- systems that do not have the considered properties; they are in the majority, and examples of them are obvious.

Among goal-oriented systems, a class is distinguished, called

¦ self-organizing- systems that can independently change their structure (sometimes composition), the degree of complexity in order to better adapt (adapt) to changing environmental conditions.

Examples: the production of protective antibodies by the body when foreign proteins enter it - antigens, for example, with pathogenic bacteria; changes in the body of a protective nature in the fight against disease, the combination of birds in flocks of a certain species before a long flight, the mobilization of their mental abilities and the behavior of students before exams, etc.

Self-organizing systems are also called self-regulating, restructuring.

5. Connections are the most important concept of general systems theory

Links -- characteristics of the interaction of elements in the system and the implementation of its structure.

This is the basic concept of OTS, in the absence (break, termination) of links, the system as a whole ceases to exist and breaks up into elements: a computer turns into a set of radio components, a house turns into a set of bricks, a living organism into a set of chemical elements (with time after death) and etc.

It is the presence of links in the system that determines its new properties, which the elements of the system do not have, even their sum. Such a super-total effect for elements connected in a system is called a system effect, or an assembly effect, or emergence (from the English “appearance of a new one”).

Examples system effect:

a) in physics: the nucleus of an atom has a reduced energy in comparison with the energy of the totality of nucleons - the elements of this nucleus;

b) in chemistry: the chemical properties of water molecules (H 2 0) differ from the chemical properties of hydrogen (H) and oxygen (O); the last without a chemical compound nothing

do not dissolve, but form an "explosive mixture";

c) in biology: the molecules of phosphoric acid, sugar (deoxyribose), nitrogenous bases, being scattered and randomly in a dissolved state in a test tube, are not capable of the birth and development of a living organism, but combined into a DNA molecule placed in a living cell, they are capable of . communication natural science molecule structure

The supertotal properties of the elements in the system, i.e., the system effect, distinguishes the system from a simple set of elements for which the principle of superposition is fulfilled, i.e., the independent manifestation of the properties of the elements (each behaves as if there were no others) and obtain a pure the total effect of their action (geometric addition of vectors of forces, velocities, accelerations, etc. - in mechanics; algebraic addition light vibrations in optics, etc.).

Thus, the connections between the elements in the system determine their mutual influence on each other, while the properties and characteristics of the elements change: some properties are lost, others are acquired. This was known to Aristotle as early as the 4th century. BC e. :

"A hand physically separated from a human body is no longer a human hand."

Relationship classification

There is a diverse classification of connections between elements, not inferior in number to the classification of systems (see above), but more complex in content. Therefore, in this section, the main types of connections will be considered with an illustration of their examples:

1) By type and purpose, communications are divided into:

genetic-- such when one element (elements) are the ancestor of another (others).

Examples: parents and children; initial substances and products of chemical reactions; series of radioactivity in atomic physics; morphogenesis of sedimentary rocks in geology; sequences of stellar transformations in astronomy, etc.;

communications interaction- such, when elements simultaneously interact, influencing each other.

Examples: nerves and muscles in organs, predators and prey in common habitats, rivers, seas and oceans of the earth's surface, engineers, technicians and workers in production, etc.;

communications management-- such when some elements of the system control the behavior of other elements.

Examples: central nervous system and peripheral organs; traffic rules and traffic flows; leaders and subordinates in the organization; etc.;

conversion links-- such when some elements affect the transition of the system from one state to another or from one structure to another.

Examples: catalysts in chemical reactions; heaters for melting substances; earthquakes in settlements; training systems in advanced training, etc. The boundaries between the listed types of connections are vague, and specific connections cannot always be attributed to a specific class.

2) By degree of action connections are divided into:

a) tough-- such, in which the action of the connection is rigidly predetermined and the result of the action of one element on another is unambiguous.

a) b)

Examples: mechanical links in a sewing machine, seams between the bones of a human skull, adhesive joints in shoes, fungal growths on trees, coal seams underground, the root system of plants in the soil, etc.;

b) flexible-- those in which the action of the connection allows some freedom in the behavior of the associated elements.

Examples: articulations, muscle groups, ocean currents, suspension bridges, book bindings, fixing glaciers and snow layers in the mountains, etc.

One should not think that rigid connections are necessarily realized through rigid mechanical units, ropes, chains, solid formations. The gravitational connection (for example, between the Sun and the Earth, the Earth and the Moon, etc.) is also rigid, although "invisible". The same can be said about the electromagnetic connection within atoms and molecules.

Of great importance in biology (zoology) are the so-called food links and even food chains. Bees eat only nectar, cows eat grass (hard connection), fish and humans are practically omnivorous (flexible connection).

3) By direction connections are divided into:

¦ straight- those in which one element affects another, without being influenced by the latter; usually the first element is dominant and the second element is subordinate.

Examples: "The order of the commander is the law for the subordinate", authoritarian leadership style; hypnotic effect of a snake on a rodent; snow avalanche coming down from the mountain; target shooting; eruption; etc.;

¦ neutral- those that have no direction; they usually exist between elements of the same type and combine them into a system.

Examples: connections between cars in the train; between molecules in a crystal; between athletes in a team; between ordinary individuals in a bird flock; between nucleons in the nucleus of an atom; etc.;

¦ reverse- such, in which one element acts on another (direct connection), while experiencing the action of the second on itself (feedback). Thus, in contrast to the direct action of the dominant element on the subordinate without a reverse influence (see above), here the reverse influence arises. There is no direct feedback.

Examples: martial arts, physiological reflexes, billiard collisions, dissolution of substances, friction of movement, evaporation of liquids in a closed vessel, etc.

Since the feedback affects the element - the source of the impact, then such an impact can, in principle, be threefold: either stimulate the impact from the source, or suppress it, or not change it. Last type of feedback practical value does not have, it can be excluded from consideration or attributed to a type of direct connection (see above). The other two types are important both in practice and in OTS.

performance feedback are divided into:

¦ positive feedbacks, in which the feedback enhances the impact of the element - the source on the receiver of the impact.

Examples: swing swing, generation of radio waves, spring melting of snow (dark clearings are more heated by the sun), forest fires, chemical chain reactions (ignition of gunpowder, etc.), atomic explosions, epileptic seizures, flu epidemics, panic in the crowd, crystallization in solutions , the growth of ravines, etc.;

¦ negative feedbacks, at which the feedback weakens the influence of the source on the receiver of the influence.

Examples: pupillary reflexes (pupil constriction in bright light, expansion in the dark), increased sweating in heat, pore closure ("goosebumps") in cold; thermostats in refrigerators, thermostats, air conditioners; saturating vapors of gases, transcendental inhibition of the brain, etc.

It should be noted that feedbacks play an important role in the functioning of natural and social systems, including technical systems. They provide regulation, self-maintenance, self-development, survival, adaptation of systems in changing environmental conditions. The role of negative feedbacks in these processes is the greatest, since they make it possible to neutralize or substantially mitigate the influence of unfavorable environmental influences on the system, especially living organisms.

Task for independent research

· Choose any natural system (biological, chemical, physical, geographical, ecological, etc.) and characterize it from the standpoint of OTS.

· How can the knowledge of OTS be applied in tourism?

ON. Lipovko. Concepts of modern natural science. Textbook for high schools. --Rostov-on-Don. From "Phoenix", 2004, p.

Bertalanffy L. vonGeneral systems theory --Critical review / In the book: Research on general theory of systems.-- M.: Progress, 1969. S. 23--82. On the English language: L. von Bertalanffy, General System Theory -- A Critical Review // "General Systems", vol. VII, 1962, p. 1--20.

Bogdanov A. A. Tectology: General organizational science.-- M.: Finance, 2003.

(The term "tectology" comes from the Greek fEchfschn - builder, creator and lgpt word, teaching).

Lektorsky V. A., Sadovsky V. N. On the principles of systems research // Questions of Philosophy, No. 8, 1960, pp.67-79.

Sedov E. A. Information-entropy properties social systems// Social Sciences and Modernity, No. 5, 1993, pp. 92-100. See also: Tsirel S. "QWERTY-effects", "Path Dependence" and the law of hierarchical compensation // Questions of Economics, No. 8, 2005, pp.19-26.

Sadovsky V. H. Ludwig von Bertalanffy and the development of systems research in the 20th century. In book: System approach in modern science. -- M.: "Progress-Tradition", 2004, p.28.

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