The ideal reference model in which the main ones are presented. Adaptive regulation on the reference model. BPM in the enterprise architecture

To match the operation of network devices from different manufacturers, ensure network interaction that use a different signal propagation environment created a reference model of interaction open Systems (BRE). The reference model is built on a hierarchical principle. Each level provides the service to the superior level and uses the services of the lower level.

Data processing begins with an application level. After that, the data pass through all the levels of the reference model, and through the physical layer is sent to the communication channel. Data reverse processing occurs.

Two concepts are introduced in the OSI reference model: protocol and interface.

The protocol is a set of rules on the basis of which the levels of various open systems interact.

The interface is a combination of means and methods of interaction between the elements of the open system.

The protocol determines the rules for the interaction of the modules of one level in different nodes, and the interface - modules of adjacent levels in one node.

In total, there are seven levels of the OSI reference model. It is worth noting that less levels are used in real stacks. For example, the popular TCP / IP uses only four levels. Why is that? Explain a little later. And now consider each of the seven levels separately.

OSI model levels:

Physical level. Determines the type of data transfer medium, physical and electrical characteristics of the interfaces, the view of the signal. This level is dealing with information bits. Examples of physical layer protocols: Ethernet, ISDN, Wi-Fi.
Channel level. Responsible for access to the transmission medium, error correction, reliable data transfer. At the reception The data obtained from the physical layer are packaged in the frames after which their integrity is checked. If there are no errors, the data is transmitted to the network level. If there are errors, the frame is discarded and a request for re-transmission is formed. The channel level is divided into two sublevels: MAC (Media Access Control) and LLC (LOCICAL Link Control). Mac regulates access to a shared physical environment. LLC provides network level maintenance. Switches operate on the channel. Examples of protocols: Ethernet, PPP.
Network level. Its main tasks are routing - determining the optimal data transfer path, logical addressing of nodes. In addition, this level may be assigned tasks for troubleshooting networks (ICMP protocol). Network level works with packages. Examples of protocols: IP, ICMP, IGMP, BGP, OSPF).
Transport level. Designed to deliver data without errors, loss and duplication in the sequence as they were transmitted. Performs through control of data transmission from the sender to the recipient. Examples of protocols: TCP, UDP.
Session level. Manages the creation / maintenance / completion of the communication session. Examples of protocols: L2TP, RTCP.
Representative level. Conducts data transformation to the desired form, encryption / coding, compression.
Applied level. Carries out interaction between the user and the network. Interact with applications on the client side. Examples of protocols: HTTP, FTP, Telnet, SSH, SNMP.

After exploring the reference model, consider the TCP / IP protocol stack.

The TCP / IP model defines four levels. As can be seen from the figure above - one level of TCP / IP can correspond to several levels of the OSI model.

TCP / IP model levels:

Network interface level. Complies with the two lower levels of the OSI model: channel and physical. Based on this, it is clear that this level defines the characteristics of the transmission medium ( twisted para, optical fiber, radio), view of the signal, encoding method, access to the transmission medium, error correction, physical addressing (MAC address). The TCP / IP model has an ETHRNET protocol and its derivatives (Fast Ethernet, Gigabit Ethernet) at this level.
The level of firewall. Corresponds to the network layer of the OSI model. Takes all its functions: routing, logical addressing (IP addresses). At this level, IP protocol works.
Transport level. Corresponds to the transport level of the OSI model. Responsible for the delivery of packages from the source to the recipient. At this level, two protocols are involved: TCP and UDP. TCP is more reliable than UDP by creating a pre-connection, retransmission requests when errors occur. However, at the same time, TCP is slower than UDP.
Applied level. His main task is to interact with applications and processes on hosts. Examples of protocols: HTTP, FTP, POP3, SNMP, NTP, DNS, DHCP.

The encapsulation is the method of packing a data packet in which the package independent service headers are abstract from the headers of the lower levels by inclusion in the superior levels.

Consider on specific example. Let we want to get from the computer to the site. To do this, our computer must prepare an HTTP request to receive a web server resources on which the site page needs us. At the application level to data (DATA) the browser adds an HTTP header. Next, a TCP header is added to our package to our package containing the sender and recipient port numbers (80 port for HTTP). On the network level The IP header is formed containing the IP addresses of the sender and the recipient. Immediately before transfer, an Ethrnet header is added on the channel level, which contains the physical (MAC addresses) of the sender and the recipient. After all these procedures, the package in the form of bits of information is transmitted over the network. Reverse procedure happens at the reception. The web server at each level will check the corresponding header. If the check has passed successfully, the title is discarded and the package goes to the top level. Otherwise, the entire package is discarded.

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Reference model

Reference model (eng. reference Model, master Model) - This is an abstract presentation of concepts and relations between them in some problem area. Based on the reference, more specific and in detail of the described models are built, as a result embodied in real-life objects and mechanisms. The concept of the reference model is used in computer science.

Examples of reference models

OSI network model (OPEN Systems InterConnection Reference Model),
model of an open geospatial consortium (eng.),
architecture von Neumanana - model of the reference model with consistent calculations,
reference model of the architecture of the State Enterprise (English),
Reference information model HL7 (Reference Information Model, RIM HL7),
Reference Model, Rm Openehr.

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Watch what is a "reference model" in other dictionaries:

reference model - Hierarchical model - [L.G.Sumenko. English Russian dictionary on information technology. M.: GP Tsniis, 2003.] Themes information Technology In general, the synonyms of the hierarchical model en Reference Model ...

reference model - Etaloninis Modelis Statusas T Sritis Automatika Atitikmenys: Angl. Master Model; REFERENCE MODEL VOK. ReferenZModell, N Rus. Reference model, F pranc. modèle de référence, m; Modèle Standard, M ... Automatikos Terminų žodynas

reference model - 3.1.41 Reference Model: Structured set of interrelated representations about the object (for example information system), covering this object In general, simplifying the breakdown of links on the subject matter, which can be ... ... Dictionary directory terms of regulatory and technical documentation

reference model - The model of interaction of open systems, developed by ISO in 1984, allows you to universally describe the logic of the information exchange between interconnected systems and subscribers. The full model contains seven levels. At the lowest ... ... Technical translator directory

reference ISO / OSI model - Seven-level reference data transfer protocol model. Determines the levels: physical, channel, network, transport, session, executive and applied. In CAN networks, only physical, channel and applied levels are usually implemented ... Technical translator directory

reference Model Broadband ISDN-Network Protocols - The model includes four horizontal levels (physical, ATM, ATM adaptation and upper levels) and three vertical planes (user, management and administration). The correspondence between models in ISDN and OSI is provided on the physical ... ... Technical translator directory

bOC reference model - EMVOS model developed by Mos, containing seven levels (layers) of protocols and intended for communication between devices on the network. [E.S. Alexseev, A.A. Muchev. Anglo Russian Explanatory Dictionary on System Studies Computer. Moscow 1993] Themes ... ... Technical translator directory

reference model of interaction of open systems - - Telecommunication Topics, Basic Concepts EN ISO / OSI Reference Model ... Technical translator directory

reference Model Protocol - - [L.G.Sumenko. English Russian dictionary on information technology. M.: GP Tsniis, 2003.] Topics Information Technologies In general, EN Protocol Reference ModulePrm ... Technical translator directory

reference Model of Open Systems - - [L.G.Sumenko. English Russian dictionary on information technology. M.: GP Tsniis, 2003.] Themes Information Technologies In general, EN Reference Model of Open Systems ... Technical translator directory

Books

Computer networks. In 2 volumes. Volume 1. Data transfer systems, R. L. Sweliansky. The theoretical foundations of data transmission systems, the characteristics of the main types of physical environments, the methods of coding and transmitting analog and digital data, the basis of the organization ...

The initial idea of \u200b\u200ba professional profession gives its structural content. In described pro-fassograms of professions, including the following sections - general characteristics professions, its meaning; Description of the employment process performed; Requirements of the profession for personality; working conditions; necessary knowledge; required skills and skills; where you can get a specialty; Economic working conditions.

There is also a professional method of studying the identity and activities of the modern teacher.

Professional - that's perfect model Teachers, teacher, class teacher, teacher, sample, standard in which:

The main qualities of the person who must have a teacher;

Knowledge, skills, skills to perform teacher functions.

Based on this understanding of the meaning of the concept of "Professional", it is possible to talk about the professional method of studying the individual, in which the knowledge of knowledge, skills and skills with those that could be in accordance with the perfect model are made of the teacher. It is not difficult to imagine that such a method allows to design a personal and professional growth of the teacher.

At the same time, the teacher's professionalism is a document in which the full qualification characteristic of the teacher is given from the standpoint of the requirements for its knowledge, skills and skills, to his personality, abilities, psychophysiological capabilities and the level of training.

Such an idea of \u200b\u200bthe profession was evolved in previous decades. So, we can talk about the profession of a class teacher, compiled by N. I. Boldyrev.

N. I. Boldyrev highlighted the priority qualities of the classroom of the class teacher: ideological, moral and civil maturity, public activity, passionateness of the profession of the teacher, love for children, humane, caring attitude towards them, high demanding to themselves and students, communicativeness, friendly location, politeness In communication, psychological compatibility with other members of the pedagogical team and others necessary for the ideal specialist.

To perform a large variety of functions, the teacher, according to N. I. Boldyrev, requires the following skills:

establish business relations with the school administration, with parents, the public (communication skills, on today's ideas close to communicative);

information skills and skills;

the ability is bright, expressive, logical to express their thoughts (according to today's ideas - didactic and speech);

the ability to convince to attract to themselves, to make their supporter (according to today's ideas - didactic, communicative).

To implement these skills, it is necessary to create a high emotional attitude, to ensure the business nature of life, labor.

An important role of N. I. Boldyrev took the qualities of the personality, which in addition to priority would be nice to have a teacher (to the class teacher): tact, excerpt, self-grade, observation, sincerity, resourcefulness, hardness, sequence in words and actions, accuracy, external tidiness .

It is important to know the basics of the theory and methodology of education, to be able to know the basics of the theory and methods of upbringing.

work with parents (public); Plan an educational work;

select on the basis of diagnostics of groups (groups), individual personalities the necessary activities;

correctly take into account and evaluate the results of upbringing; identify and organize asset;

control and assistance in the execution of orders.

To fulfill complex and diverse functions, teacher would be good to master some applied creative art skills:

draw (pictorial);

play musical instruments, sing (musical); expressively read (artistic literary); dance (choreographic);

go hiking (sports and tourist or sports and labor).

A. S. Makarenko in the opening of the word to the "Book for Parents" wrote: "The ability to educate is still an art, the same art, how to play a violin or piano, to write pictures well, to be a good millover or tokar."

If you go from the functional principle, i.e. from the actions of the functions that the teacher must perform, then you can re-coursize the functions of the teacher. So, among the first (in 1971), the eight functions of the teacher at school A. I. Shcherbakov, N. A. Rykov allocated. They belong to the following classification of teacher functions:

Information (teacher broadcasts one infor);

Developing (develops thinking, imagination, certain skills, speech, etc.);

orienting (orients in the manifold of information, moral values);

mobilization (mobilizes for exercises, tasks, cases);

constructing (design lesson, extracurricular business, multi-level tasks, independent work, communication and much more);

communicative (communication feature with parents, other teachers, administration, psychologists, valeologists, etc.);

organizational (organizes students, other teachers, parents, itself, and also organizes lessons, extracurricular cases, which conducts);

research (knows how to explore both a separate personality, a group of students - the team and the training and educationalness of students, etc.).

Mentioning the last function, from our point of view, allows us to talk about the functions not only the teacher, but also a teacher - in the broad sense of the word.

In the textbooks of the Pedagogy of the past years, the authors allocate the functions of the teacher, the class teacher:

organizational (organizes all educational influences and interactions in the collectives, including in the form of educational cases - excursions, trips, meetings, class hours, questionnaires as a study, etc.);

educational (as a result of which various paths and means, education, the formation and development of the identity qualities inherent in the student as a member of the children's team, family man, a citizen of Russia, a citizen of the world, creative personality and individuality);

stimulating (as a result of which it is carried out by the influxing activity of students, children's team, parents, public, etc.);

coordination (as a result of which coordination activities of both children are coordinated when it is necessary and teachers working in one class, parallels, and can also communicate with the outside world if the educational institution is considered as an open system;

work with documents (magazines, diaries of students, their personal affairs, various plans).

Functions that must be performed by teachers, educators, cool leaders, quite a lot. What knowledge and skills should they possess? The idea of \u200b\u200bthe skills and skills that the teachers should have, and cool leaders, gives the concept of the professors considered by us above. However, just knowledge and skills mentioned earlier, not enough. As psychologists consider, much depends on natural prerequisites, personal deposits (which can develop in certain abilities), from the psychological readiness of the person, its aspirations (desires) to perform these functions. Much is brought up, produced only as a result of long work on themselves; The main thing in self-education is patience and control over your behavior.

Psychologist V. A. Kruttsky in the textbook "Psychology" offers the structure of professional and significant qualities of the person and skills that must be had to have a teacher. If the professionally significant qualities of the teacher's personality, we will be presenting in the form of a combination of four blocks (parts or substructures) (1. The worldview of the personality; 2. Positive attitude to pedagogical activities; 3. Pedagogical abilities; 4. Professional-pedagogical Knowledge, skills and skills), we will get a sufficiently holistic idea of \u200b\u200bthe requirements that are presented to the teacher's profession and other pedagogical professions.

Consider these blocks professionally important qualities of the teacher's personality.

1st block. Humanistic worldview ( we are talking about those convictions, ideals that are inherent in the teacher to teacher; only the one who is raised himself; It is desirable that the educator has high level General culture and high moral appearance, and most importantly - love other people).

2nd block. Positive attitude to pedagogical activities (we are talking about the pedagogical orientation of the person, pedagogical inclinations as a sustainable desire and desire to devote themselves to pedagogical activities; there can be no good teacher who indifferently refers to his work; children are unmistakably determine those teachers who do not like them or Do not love pedagogical activity as a whole).

3rd block. Pedagogical abilities (based on natural prerequisites, they are implemented under certain conditions - or not - in professional-pedagogical knowledge, skills, skills, in other words - pedagogical abilities) is a generalized set of individual-psychological features and professional-meaningful personal qualities that respond The requirements of pedagogical activity, ensure the achievement of high results, determine the success of the teacher as a whole in mastering this activity (for details, see ch. 1).

4th block. Professionally and pedagogical knowledge, skills, skills (we are talking about knowledge of the subject of the subject and technology of learning).

V. A. Sukhomlinsky mentions four signs pedagogical culture. Briefly his thoughts can be expressed like this. Necessary: \u200b\u200b1) In order for the teacher to have academic knowledge, so that you can turn to the mind and heart of the pupil; 2) so that the teacher read the literature (pedagogical, psychological, journalistic, etc.); 3) In order for the teacher to know the wealth of the methods of studying the child; 4) possessed a speech culture.

So, experts believe that good prerequisites for becoming a teacher, possess those who.

The model with an ideal point involves a comparison of a particular product or other object with some standard in the form of a difference. In accordance with the model, each feature is normalized as a distance from the ideal or reference character value. For the application of the model, the ideal of the product is primarily formed in terms of the product - the "ideal" point x0 is introduced.

The model gives a characteristic of the degree of proximity of a particular product to the "ideal" in accordance with addiction

where TO i. – Weight coefficients; H. 0i. – The coordinates of the ideal point. Exponent t. selected by the researcher and, as a rule, takes values \u200b\u200bat level 1 or 2. The summation is carried out by p Product properties. Best are low W, Because if the perfect point is the best, it is obvious that it is desirable that the minimum distance from it is desirable.

The choice of an ideal point is quite complicated and ambiguous. The reader should pay attention to the following possible approaches to the choice of the perfect point.

1. Best expression points: "All fives." If you consider such a consumer sign as convenience of controlling complex equipment, such as a car or music CenterThe coordinates of the ideal point will correspond to the boundary of the selected scale. However, the corresponding hypothetical "best in all respects" the product will be far from reality, since it is not always the best product in all parameters. In particular, it is difficult to combine the properties of a limousine and an SUV in one car. If the best product still exists, then it will be excessively high.
2. Apply the parameters of the real most competitive or "best on the market" of the product according to the principle: "My dream girl" or "a real man." The peculiarity of this approach is that they are considered unwanted deviations from the perfect point to any side, even towards the formal improvement.
3. The use of such objective properties when there is an optimal level of property. In this case, the ideal levels will not necessarily be either the largest, or the smallest. In such a situation, the application of the model with an ideal accurate is most substantiated. Examples of parameters with optimum: The size of the TV screen for the car or kitchen, the brightness of the television image. Good example presence optimal level It is the illumination of the room, when "too bright" and "too dark" is equally undesirable. It should be done about the need to specify the purpose of the product. So, if you do not specify that the TV is designed for the kitchen, then the desire may occur to consider the perfect large TV from those that are on sale.
4. Best properties at the price. The following approach is offered. In order not to put "all fives", which in principle is not required, and it is not unrealistic for the price, it is necessary to have a regression model of the price dependence on the levels of properties, which corresponds to parametric pricing. Then the expert can choose a set of properties with each price available for it. And this is real, since the approach "Mobile should not cost more than ten thousand" applied by many.

Obviously, to use a model with an ideal point of dimension of all coordinates, the coordinates must coincide in order to be able to summarize the corresponding values \u200b\u200bin the formula. One output from the problem is the use of dimensionless points. Another way that is considered further is normalization when the actual levels are divided into reference or regulatory, which can also be the coordinates of the ideal point.

Model with normalized levels of factors

The use of models with relative factors allows in one model to combine factors with different dimensions. The corresponding model has the following form:

(16.2)

All designations correspond to the (16.1) introduced in formula (16.1); Zi - parametric indexes.

The model is widely used when calculating product quality indices and, especially when evaluating competitiveness. When calculating quality indices H. i0 - Regulatory, specified by the standards and specifications, the level of severity of product properties. As a rule, model (16.2) is used while simultaneously considering the objective (production and operational) properties of the product, such as speed, power, dimensions, reliability, etc., although it is possible to consider objective properties.

When evaluating competitiveness H. i0. – The parameters of the compared product, which can be the product of the strongest competitor. In the literature on competitive analysis there are various names of the indicator - a consumer parameter index of consumer properties, a group of competitiveness.

Classification of models

The problem of classifying models, like any sufficiently complex phenomena and processes, complex and multifaceted. The objective reason for this is that the researcher is only interested in some kind of property (or several properties) of the system (object, process, phenomena), to display which the model is created. Therefore, the basis of the classification can be put in many different classification features: a method of description, functional purpose, degree of detail, structural properties, scope, etc.

Consider some of the most frequently used classes (species) of models (Table 1.4.1).

Table 1.4.1

Sign of classification	Types of models
The essence of the model	- Material (physical) - ideal (imagined) - information (theoretical, abstract)
Characteristics of the modeling object	- model external view - Model model - model of behavior
The degree of formalization	- informalized - partially formalized - formalized
Appointment model	- Research :. Descriptor. Cognitive. Conceptual. Formal - training - workers :. Optimization. Management
Role in managing the object of modeling	- registering - reference - prognostic - imitation - optimization
Time factor	- Static - Dynamic

Material(physical, real) models - models built by means of material world to reflect its objects, processes.

Ideal(imagined) models - models built by means of thinking on the basis of our consciousness.

Information(Abstract, theoretical) models - models built on one of the languages \u200b\u200b(iconic systems) of information encoding.

Material modelsthere are real, real designs that serve to replace the original in a certain relation. The main requirement to build this class of models is the trend in the similarity (similarity, analogy) between the model and the original. There are several types of similarity - geometric, physical, analogy, etc.

Geometric similarityit is the main requirement for the construction of geometric models, which are an object, geometrically similar to its prototype and serving for demonstration purposes. Two geometric shapes are similar if the ratio of all the corresponding lengths and angles is the same. If the similarity ratio is known is the scale, then the sizes of another figure are determined by the simple multiplication of the size of one figure. In the general case, such a model demonstrates the principle of operation, the mutual location of the parts, the process of assembling and disassembly, the layout of the object and is intended to study the properties that are invariant (independent) from the absolute values \u200b\u200bof the linear dimensions of the object. Examples of geometric models are: Magnets of machinery, mannequins, sculptures, prostheses, globes, etc. They depict the prototype not in the entire variety of its properties, not in any quality borders, but within the boundaries of pure spatial. There is a similarity (like) not at all between things, but between the special types of things - bodies. This is the limitations of this class of models. Note that a direct similarity is implemented here.

Physical semblanceit refers to the model and the original of the same physical nature and reflects their similarity in the same relationship between the physical variables of the corresponding space-time points. Two phenomena are physically like if, according to the specified characteristics of one, it is possible to obtain the characteristics of another simple recalculation, which is similar to the transition from one system of units of measurement to another. The geometric similarity is a special case of a physical similarity. With a physical similarity, the model and the original may be in more complex geometric relations than linear proportionality, since the physical properties of the original are not proportional to its geometrical sizes. It is important here that the space of physical variable models is similar to the space of physical variables of the original. At the same time, the physical model in relation to the original is an analogy of the type of isomorphism (mutually unambiguous compliance). The central problem is the problem of correct recalculation of the results of the model experiment on the test results of the original in real conditions. The similarity is based on compliance with some physical criteria.

Ideal(Imagined) models are ideal designs in our consciousness in the form of images or ideas about certain physical phenomena, processes, objects, systems (geometric point, infinity, etc.).

Abstract(Theoretical, information) models - models representing modeling objects in a figurative or sign form.

Examples of abstract models can serve as any hypothesis 1 on the properties of matter, assumptions about the behavior of a complex system in conditions of uncertainty or a new theory about the structure of complex systems.

On abstract models and at the speculative analogy (similarity) between the model M.and origal S.abstract (theoretical) mode-lying is built.

A bright representative of abstract and iconic modeling is a mathematical model.

Mathematical model– this is a totality mathematical formulas, equations, relationships that describe the properties of the modeling object of interest.

To study each aspect of modeling (species, structure, behavior) or their combination, the corresponding models can be used: models of appearance, model model, model behavior.

Model of appearancemost often reduces to transfer external features of the modeling object and is intended for identifying an object (recognition) of the object.

Model structureit is a list of composite elements of the modeling object with the links between these elements and is intended for a visual display, the study of properties, identifying significant connections, studies of the stability of the modeling object.

Model of behaviorit is a description of changes in the appearance and structure of the modeling object over time and as a result of interaction with other objects. Purpose of behavior models - forecasting the future states of the modeling object, object management, the establishment of links with other objects, external relative to the modeling object.

Objectively, the levels of our ideas, the levels of our knowledge of various phenomena, processes, systems are different. This is reflected in the methods of representing the phenomena under consideration.

TO informalized models include mappings (images) obtained using various forms of thinking: emotions, intuition, figurative thinking, subconscious, heuristics as a set of logical techniques and the rules for finding truth. With informalized modeling, the model is not formulated, and instead it uses some fuzzy mental reflection (image) of reality, which serves as the basis for making a decision.

An example of indefinite (intuitive) ideas about the object can be a fuzzy description of a situation based on experience and in-tuition.

TO formalized models include figurative models when the models are built from any visual elements (elastic balls, fluid flows, body trajectories, etc.).

Formalizable abstract models include signal models, including mathematical designs, programming languages, natural languages \u200b\u200btogether with the rules of their transformation and interpretation.

In its purpose, the model is designed to solve many tasks:

research(descriptory, cognitive, conceptual, formal) models are designed to generate knowledge by studying the properties of the object;

trainingthe models are designed to transfer knowledge about the object being studied;

workers(optimization, managerial) models are designed to generate right action In the process of achieving the goal.

TO research models include semi-industrial stands, physical models, mathematical models. Note that research-Tel models can act as training if they are presented to transfer knowledge about the properties of the object. Examples of working models can serve: robot; autopilot; Mathematical model of an object built into the control system or control; Artificial heart, etc. At the same time, research and training models should approach reality, and working models should reflect this reality. There is no clear boundary between these models. For example, a research model, adequately reflecting the properties of the object, can be used as a working.

Research models are carriers of new knowledge, training models combine old knowledge with new ones.

Working models idealize accumulated knowledge in the form of ideal actions to perform certain functions that would preferably be implemented.

Descriptor models- Descriptive models are intended to establish laws change the parameters of these processes and are implementations of descriptive and explanatory meaningful models at the formal modeling level.

As an example of such a model, you can cite a model of the material point under the action of the applied forces using the second law of Newton. By setting the position and speed of the point at the initial moment of time (input values), the point of the point (model parameter) and the law of changing the forces applied (external influences), you can determine the speed and coordinates of the point at any subsequent point in time (output values).

Cognitive(mental, cognitive) models - Models that are a certain mental image of the object, its ideal model in the head of the researcher, obtained as a result of monitoring the object-original.

Forming such a model, the researcher, as a rule, seeks to answer specific questions, therefore, from an infinitely complex device of the object, everything is unnecessary in order to obtain its more compact and concise description.

Cognitive models are subjective, as they are formed speculatively based on all previous knowledge and experience of the researcher. You can only get an idea of \u200b\u200ba cognitive model only describing it in a mark form. The presentation of the cognitive model in a natural language is naughty content model .

Cognitive and meaningful models are not equivalent, since the first may contain elements that the researcher cannot or do not want to formulate.

Conceptual modelit is customary to be called a meaningful model, with the wording of which the concepts and representations of subject areas of knowledge engaged in the study of the modeling object are used.

In a broader sense, the conceptual model understands a meaningful model based on a certain concept or point of view.

Formal modelis a submission conceptual model With one or more formal languages \u200b\u200b(for example, languages \u200b\u200bof mathematical theories, a universal model of modeling or algorithmic languages).

In the humanities, the modeling process in many cases ends with the creation of a conceptual model of the object.

In natural-scientific and technical disciplines, as a rule, it is possible to build a formal model.

Thus, cognitive, meaningful and formal models constitute three interrelated levels of modeling.

Optimization models- Models intended to determine the optimal (best) from the point of view of a certain criterion of the parameters of the simulated object or to search for the optimal (best) control mode of some process.

As a rule, such models are constructed using one or more descriptive models and include some criterion to compare various options for sets of output values \u200b\u200bamong themselves in order to choose the best. The area of \u200b\u200binput parameters values \u200b\u200bmay be imposed on the form of equalities and inequalities associated with the features of the object under consideration or process.

An example of an optimization model can be modeling the rocket launch process from the ground surface in order to raise it to a given height for minimumtime with restrictions by the magnitude of the engine pulse, time of its operation, the initial and final mass of the rocket. The mathematical ratios of the descriptive model of the rocket movement act in this case in the form of limitations of the type of equalities.

Note that for most real processes, designs requires definition optimal parameters Immediately in several criteria, i.e. We are dealing with the so-called multi-criteria optimization tasks.

Management models- Models used to make effective management decisions in various fields of targeted human activity.

In general, making decisions is a process, in its complexity compared with the process of thinking as a whole. However, in practice, the adoption of decisions is usually understood as the choice of some alternatives from the specified sets of their set, and the overall decision-making process is represented as a sequence of such elections alternatives.

Unlike optimization models, where the selection criterion is considered a certain and the desired solution is established from the conditions of its extremality, in management models it is necessary to introduce specific optimal criteria that allow you to compare alternatives at various uncertainties of the task. The type of optimality criterion in managerial models is not fixed in advance. This is the main feature of these models.

Registering modelsthere are models designed to register the properties and qualities of interest to directly register on the modeling object.

When solving tasks of controlling complex dynamic objects, reference and predictive models are used, which are a formalized display of the desired characteristics of the control object for the purposes of the current or future object control.

Reference model- This is a model describing the desired (idealized) properties of the modeling object (control) in one form or another.

Prognostic models- Models intended for determination futurestates ( futurebehavior) modeling object.

Imitation models- This is a combination of the description of the elements of the system, the relationships of the elements with each other, external influences, the functioning algorithms of the system (or rules for state changes) under the influence of external and internal perturbations.

Simulation models are created and used when the creation of a unified model of a complex system is impossible or associated with very large difficulties available. mathematical methods Do not allow satisfactory analytical or numerical solutions to the tasks under consideration. But the presence of descriptions of elements and functioning algorithms allows you to imitate the process of functioning of the system and produce measurementscharacteristics of interest.

It can also be noted that imitation models can be created for a much wider class of objects and processes than analytical and numerical models. In addition, since it is used to implement, as a rule, computing means (computers and other means) by means formalized description Imitation models are universal or special algorithmic languages.

Simulation modeling when learning large (complex) systems

it remains almost the only one affordable method for obtaining information on the behavior of the system in conditions of uncertainty, which is especially important at the stage of its design. This method can be selected by the structure, parameters and control algorithms of the synthesized system, evaluate their effectiveness, as well as imitate the behavior of the system in conditions that cannot be reproduced on the real prototype (for example, accidents, failures, emergencies, etc.). When, with simulation modeling, the behavior of the system under the action of random factors, followed by the statistical processing of infor-formation, is advisable as a method of machine implementation of the simulation model to use the static modeling method. At the same time, the method of statistical tests (Monte Carlo method) is considered as a numerical solution of solving analytical tasks.

Special class of models make up cyberneticmodels that reflect managerial aspects of the behavior of complex systems based on the informational exchange between its elements. The physical nature of cybernetic models itself differs from the physical nature of the prototype and its elements. A feature of cybernetic models is the possible presence in them, except for the control mechanism, also mechanisms for self-organization, training, adaptation, etc., and in more complex systems - and artificial intelligence.

Accounting of the time factor in modeling results in the use of static and dynamic models.

Static modelsreflect the installed (equilibrium) modes of operation of the system;

Static modes of operation of elements, objects, systems are reflected in their static characteristics (linear, nonlinear) and are described by the corresponding algebraic functional dependencies.

Dynamic modelsreflect the unidentified (nonequilibrium, transitional) modes of operation of the system.

To describe non-equilibrium (transitional) modes of operation of the system, differential equations or systems of differential equations are most often used.

Consider some properties of models that allow one to or both to distinguish or identify the model with the original (object, process). It is customary to allocate the following properties of models: adequacy, complexity, limb, truth, approximate.

Adequacy.Under adequacythe models are customary to understand the correct qualitative and quantitative description of the object (process) along the selected set of characteristics with some reasonable degree of accuracy.

Adequacy is an essential requirement for the model, it requires the correspondence of the model of its real object (process, system, etc.) relative to the selected set of its properties and characteristics. In this case, there is an adequacy in general, but adequacy for those properties of the model that are substantial for the researcher. Full adequacy means identity between the model and the prototype.

The mathematical model may be adequate for one class of situations (system status + state of the external environment) and is not adequate relative to the other. The use of an inadequate model can lead either to substantial distortion of the real process or properties (characteristics) of the object being studied, or to the study of non-existent phenomena, properties and characteristics.

It is possible to introduce the concept of degree of adequacy, which will vary from 0 (lack of adequacy) to 1 (complete adequacy). The degree of adequacy characterizes the proportion of the model relative to the selected characteristic (properties) of the object being studied. Note that in some simple situations, the numerical assessment of the degree of adequacy does not represent much difficulty. The difficulty of evaluating the degree of adequacy in the general case arises due to the ambiguity and fuzziness of the adequacy criteria themselves, as well as due to the difficulty of choosing those features, properties and characteristics by which adequacy is evaluated.

The concept of adequacy is a rational concept, therefore the increase in its degree should also be carried out at the rational level. The adequacy of the model should be checked, monitored, to be clarified continuously in the process of research on private examples, analogies, experiments, etc. As a result of an adequacy test, they find out what the assumptions made allowed: whether to the permissible loss of accuracy, or the loss of quality. When verifying adequacy, it is also possible to substantiate the legality of the application of adopted working hypotheses when solving the problem under consideration or problem.

Easy and complexity.The simultaneous requirement of simplicity and adequacy of the model is contradictory. From the point of view of adequacy, complex models are preferable to simple. In difficult models, you can take into account the larger number of factors affecting the characteristics of objects studied. Although complex models and more accurately reflect the simulated properties of the original, but they are more cumbersome, hard-seeing and uncomfortable in circulation. Therefore, the researcher seeks to simplify the model, as simple models are easier to operate. When descending to building a simple model, the main principle of simplification of the model:

it is possible to simplify the model as long as the main properties, characteristics and patterns inherent in the original are preserved.

This principle indicates a simplification limit.

In this case, the concept of simplicity (or complexity) of the model is the concept of relative. The model is considered quite simple if modern means of research (mathematical, information, physical) make it possible to conduct high-quality and quantitative analysis with the required accuracy. And since the possibilities of research funds are continuously growing, then those tasks that were previously considered complex, can now be attributed to the category of simple.

A more difficult task is to ensure the simplicity / complexity of the model of a complex system consisting of separate subsystems connected to each other into some hierarchical and multi-associated structure. At the same time, each subsystem and each level have its own local criteria for complexity and adequacy other than the global criteria of the system.

With the aim of less adequacy, simplification of models is more expedient to carry out:

1) at the physical level while maintaining the main physical relations,

2) at the structural level while maintaining the main system properties.

The simplification of models on the mathematical level can lead to a significant loss of degree of adequacy. For example, the truncation of the characteristic high-order equation to 2-3rd orders can lead to completely incorrect conclusions about the dynamic properties of the system.

Note that simpler models are used when solving the problem of synthesis, and more complex exact models - When solving the task of analysis.

Limit of models.It is known that the world is infinite, like any object, not only in space and in time, but also in its structure (structure), properties, relations with other objects. Infinity is manifested in the hierarchical structure of systems of various physical nature. However, in the study of the object, the researcher is limited to the final amount of its properties, connections used by resources, etc. He, as it were, "cuts out" from the infinite world some finite fragment in the form of a specific object, system, process, etc. And he is trying to know the endless world through the final model of this fragment.

The limb of models of systems is, firstly, in the fact that they reflect the original in the end of the relationship, i.e. With a finite number of links with other objects, with a finite structure and finite number of properties at a given level of study, research, descriptions, disposable resources. Secondly, the resources (information, financial, energy, temporary, technical, etc.) modeling and our knowledge as intelligent resources are finite, and therefore objectively limit the possibilities of modeling and the process of knowing the world through the models. Therefore, the researcher (with rare exception) is dealing with finite-dimensional models.

The choice of the dimension of the model (its degree of freedom, variable state) is closely related to the class of solved tasks. The increase in the dimension of the model is associated with the problems of complexity and adequacy. It is necessary to know what is the functional dependence between the degree of complexity and the dimension of the model. If this dependence is power, then the problem can be solved by applying computing systems. If this dependence is exponential, then the "Dimension Curse" (R. Kalman 1) is inevitably and to get rid of it almost unable.

As noted above, an increase in the dimension of the model leads to an increase in the degree of adequacy and at the same time as a complication of the model. At the same time, the degree of complexity is limited by the possibility of operating with the model, i.e. Those means of modeling that the researcher has. The need to move from a coarse simple model to more accurately implemented by increasing the dimension of the model by attracting new variables, qualitatively different from the main and those neglected when constructing a rough model. These variables can be attributed to one of the following three classes:

1) frequencyvariables whose length in time or in space is so small that with rough consideration they were taken into account by their integral or averaged characteristics;

2) medlene-trapvariables, the length of which is so great that in coarse models they were considered permanent;

3) small variables(Small parameters), the values \u200b\u200band influences of which on the main characteristics of the system are so small that they were ignored in coarse models.

It should be noted that the separation of a complex movement of the speed system to the speed-tracting and slow-lending movement makes it possible to study them in a rough approximation independently of each other, which simplifies the solution of the initial problem. As for small variables, they are neglected usually when solving the problem of synthesis, but try to take into account their influence on the properties of the system when solving the analysis problem.

When modeling, they strive to distinguish a small number of main factors, whose influence of one order and is not too difficult to describe mathematically, and the influence of other factors is possible to take into account with the help of averenen, integral or "frozen" characteristics.

Approximate models.From the above, it follows that the limb and simplicity (simplicity) of the model characterize qualitydifference (on the structural level) between the original and model. Then the approach of the model will characterize quantitativethe side of this difference.

You can enter a quantitative measure of approaching by comparison, for example, a coarse model with a more accurate reference (full, perfect) Mo-Del or with a real model. Model approximate to the original inevitable, There is objectively, since the model as another object reflects only the individual properties of the original. Therefore, the degree of approximity (proximity, accuracy) of the model to the original is determined by the formulation of the problem, the purpose of modeling.

The excessive desire for increased accuracy of the model leads to its significant complication, and, consequently, to a decrease in its practical value. Therefore, apparently, the principle of L. Zade 1 is true that when modeling complex (human-machine, organizational) systems, accuracy and practical meaning are incompatible and exclude each other. The reason for the inconsistency and incompatibility of the requirements of the accuracy and practicality of the model lies in the uncertainty and the fuzziness of knowledge about the original behavior - its behavior, its properties and characteristics, about running ambient, On the mechanisms of formation of the goal, paths and means of its achievement, etc.

The truth of the models.In each model there is a share of truth, i.e. Any model in something correctly reflects the original. The degree of truth of the model is detected only with its practical comparison with the original, for only

practice is the criterion of truth.

On the one hand, in any model, it is definitely true, i.e. definitely known and correct. On the other hand, the model contains and conditionally true, i.e. Rule only under certain conditions. A typical modeling error lies in the fact that researchers use certain models without checking the conditions of their truth, the boundaries of their applicability. This approach leads to knowing incorrect results.

Note that in any model also contains an allegedly true (plausible), i.e. Something that can be in conditions of uncertainty is either true or false. Only in practice the actual ratio between true and false in specific conditions is established. Thus, when analyzing the level of truth model, it is necessary to find out:

1) accurate, reliable knowledge;

2) knowledge, reliable under certain conditions;

3) knowledge valued with some degree of uncertainty;

4) knowledge that cannot be estimated even with some degree of uncertainty;

5) ignorance, i.e. What is unknown.

Thus, the assessment of the trueness of the model as a form of knowledge comes down to identifying the content in it as an objective reliable knowledge, correctly reflecting the original and knowledge, approximately evaluating the original, and also what constitutes ignorance.