Mathematical Remodeling Concept in Simulation of Complicated Variable Structure Transportation Systems
Autor: | Alexander Galkin, Semen Blyumin, Pavel Saraev, Anton Sysoev |
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Rok vydání: | 2020 |
Předmět: |
050210 logistics & transportation
Training set Inertial frame of reference Computer science 05 social sciences Simulation modeling 0211 other engineering and technologies Control engineering 02 engineering and technology Software implementation law.invention law 021105 building & construction 0502 economics and business Torque Feedforward neural network Transformer Intelligent transportation system |
Zdroj: | Transportation Research Procedia. 45:475-482 |
ISSN: | 2352-1465 |
Popis: | Mathematical Remodeling is aimed at transforming mathematical or simulation models of one or different classes (or subsystems forming a studied system) into a model of one predefined unified class. Depending on the goals and specific applications, different interpretations of remodeling are possible. Theoretical model constructed based on its physical meaning, can be quite complicated and is not suitable for further analysis. In this case, an array of input and output training data (which could not be obtained in real conditions) can be generated using the software implementation of the model. Using these obtained values and according to Remodeling concept it is necessary to determine a new model of a given structure with the required accuracy, which can approximate the original model in the best way. The paper presents examples of applying Mathematical Remodeling concept to constructing a dynamic system with a variable structure. Such systems are used to simulate an inertial torque transformer, which is a part of a stepless car transmission. Another example of this approach is the method of estimating freeway section capacity. Feedforward neural networks are used as remodeling classes in both cases. The introduced applications of Mathematical Remodeling approach are in the basis of constructing intelligent transportation systems. |
Databáze: | OpenAIRE |
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