NETWORK MODELS AS A SOLUTION FOR COMPLEX TECHNICAL PRODUCT`S DIAGNOSING PROBLEMS SOLVING

2019 ◽  
pp. 38-42
Author(s):  
S. Yu. Strakhov ◽  
A. A. Karasev
Keyword(s):  
Complex System ◽  
System Analysis ◽  
Network Models ◽  
Functional Testing ◽  
Formal Models ◽  
Mathematical Apparatus ◽  
Complex Technical Systems ◽  
Technical Systems ◽  
Formalized Description ◽  
Diagnostic Software

Authors explore issue of applicability of the methodology of building diagnostic software using network formal models in the functional testing of electronic equipment as part of complex technical systems. Using methods of system analysis allows to perform a decomposition of interdependent subsystems and to reveal basic acts of interaction between the control‑verification equipment and the object of diagnosis. Mathematical apparatus of Petri nets should be employed for the formalized description of such acts and determined the cause‑and‑effect relations in the diagnosed complex system`s processes. Network models properties studying (such as safety and accomplishment of the final positions) allows us to move to the test object`s algorithm`s developing. The article presents an approach of a formalized description for basic acts of interaction between the diagnosis system and the object.

Numerical methods in construction

2018 ◽  
Author(s):  
Владимир Чемодуров ◽  
Vladimir Chemodurov ◽  
Элла Литвинова ◽  
Ella Litvinova
Keyword(s):  
Numerical Methods ◽  
Differential Equations ◽  
Strain State ◽  
System Analysis ◽  
Dynamic Loads ◽  
Analytical Models ◽  
Building Structures ◽  
Structural Elements ◽  
Complex Technical Systems ◽  
Technical Systems

The monograph deals with the development of models of stress-strain state of structural elements, the study of the behavior of building structures under the influence of dynamic loads using differential equations; methods of discretization of analytical models of the functioning of building structures and design of complex technical systems (system analysis problems). It is intended for scientific and technical workers, it will be useful to students in the areas of training 08.03.01 and 08.04.01 "Construction".

scholarly journals Cascade-hierarchical modeling in analyzing the dynamics of complex system resource characteristics

2020 ◽  
pp. 48-58
Author(s):  
Yuliya Doronina ◽  
Aleksandr Skatkov
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Hierarchical Modeling ◽  
Model Complexes ◽  
Hierarchical Topology ◽  
Model Complex ◽  
Complex Technical Systems ◽  
Technical Systems ◽  
Resource Characteristics ◽  
System Characteristics

Introduction: Describing the dynamically changing resource characteristics of a complex system makes it necessary to decompose the optimization problems and itemize the system representation levels. This leads to multi-model approaches. In problems which require the construction of multi-model complexes with sophisticated links between the models, the sole use of hierarchical topology of model complexes does not guarantee that the modeling dynamics factors are connected and the data volume is taken into account at each hierarchical level. It also does not reflect the parametric variability of experiments at each level. Purpose:  Developing a technique for constructing multi-model complexes within cascade-hierarchical structures, and forming the evaluation functionality taking into account the principle of its permanence for modeling the resource characteristics of complex systems when studying the dynamics of degradation failures and replacement of resources. Methods: System analysis and structural synthesis of models; embedded Markov models with quasi-absorbing state at the local level of a multi-model complex. Results: The principle of permanent evaluation functionality is formulated. It allows you to implement an approach to the problems of decision support for resource provision in complex technical systems by determining the service strategy. In general, a cascade-hierarchical modeling scheme is formed in a three-dimensional functional space: system structure — model type (level)  — modeling plan cascades. The proposed modeling methodology within the cascade-hierarchical topology of a multi-model complex on the base of the permanent evaluation functionality principle allows you to keep the constancy of the representability of system characteristics under the phase enlargement of the modeling space, and thereby rationalize the planning of your experiments. Practical relevance: The results of the research were used in the development and analysis of the dynamics of resource security of complex technical systems. The proposed approach makes it possible to formulate research plans for complex systems in a parametric model space and, based on the principle of the permanent evaluation functionality, keep the constancy of the representability of system characteristics under the phase enlargement of the modeling space.

Assessment of the Economic Efficiency of Training Complex System Operators

2021 ◽  
pp. 65-70
Author(s):  
Syergyey Logvinov ◽  
S. Logvinov
Keyword(s):  
Complex System ◽  
Economic Evaluation ◽  
Economic Efficiency ◽  
Individual Characteristics ◽  
Complex Technical Systems ◽  
Technical Systems ◽  
Effectiveness Of Training

The possible ways of economic evaluation of the effectiveness of training operators to manage complex technical systems are analyzed. The variants of evaluation are considered, taking into account the achievement of a given level of reliability when performing management tasks, the professional suitability of operators for this type of activity based on their individual characteristics and the characteristics of the tasks being solved.

scholarly journals Skill Oriented Online Master’s Course “Neural Network Modeling of Complex Technical Systems”

2020 ◽  
Vol 35 ◽  
pp. 01011
Author(s):  
Ekaterina V. Panfilova
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Modeling ◽  
Research Work ◽  
Network Models ◽  
Neural Network Modeling ◽  
Neural Network Models ◽  
Study Results ◽  
Complex Technical Systems ◽  
Technical Systems

In this paper we consider the application of online course “Neural Network modeling of Complex Technical Systems” in the Master’s degree programs in the field of nanotechnology and nanoengineering in Bauman Moscow State Technical University. The course has rather practical than theoretical nature. The aim of this course is skill oriented learning. Nowadays neural network models have become a powerful tool of scientific research for engineers and students. The methods studied during the study of the discipline can be applied to estimation, modeling, classification, clustering, forecasting and more. The neural networks modeling plays a significant role in Master’s education and student’s research work. Neural Networks models are successfully presented in graduation theses. Thanks to online educations students can practice at their own pace and study modern neural networks software products, methods of data preparing, designing and training neural network and then apply these algorithms in practice. According to the steps of neural network modeling algorithm the course consists of three main parts and conclusive one. In this paper course structure and study results are presented.

Knowledge representation in graph-models of complex technical systems

2020 ◽  
pp. 12-16
Author(s):  
Evgenia R. Muntyan
Keyword(s):  
Analytical Study ◽  
Level Structure ◽  
Graph Models ◽  
Level Data ◽  
Knowledge Formation ◽  
Different Types ◽  
Level Information ◽  
Complex Technical Systems ◽  
Technical Systems ◽  
Structure Of Knowledge

The article analyzes a number of methods of knowledge formation using various graph models, including oriented, undirected graphs with the same type of edges and graphs with multiple and different types of edges. This article shows the possibilities of using graphs to represent a three-level structure of knowledge in the field of complex technical systems modeling. In such a model, at the first level, data is formed in the form of unrelated graph vertices, at the second level – information presented by a related undirected graph, and at the third level – knowledge in the form of a set of graph paths. The proposed interpretation of the structure of knowledge allows to create new opportunities for analytical study of knowledge and information, their properties and relationships.

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