EVOLUTIONARY MODELING PROBLEMS IN STRUCTURAL SYNTHESIS OF INFORMATION NETWORKS OF AUTOMATED CONTROL SYSTEMS

Abstract
This paper provides a new approach for solving a problem of modeling and structural syntheses of information networks of automated control systems by applying fuzzy sets theory, fuzzy logic and genetic algorithms. The procedure of formalizing structural syntheses of multi-level dispersed information networks of automated control systems is proposed. Also, the paper proposes a conceptual model of evolutionary syntheses based on genetic algorithms, which do not require additional information about the characteristics and features of target function. Modified genetic operators of crossover, mutation and algorithms of evolutionary syntheses of information networks systems are developed. Finally, the results of computational experiments on researching the influence of probability of the use of crossover and mutation operators, method of choosing parental pairs, and the size of initial population on the speed and precision of final results are provided.

Authors
N. R. Yusupbekov, A. R. Marakhimov, S. M. Gulyamov, J.H. Igamberdiev
Tashkent State Technical University, Tashkent, Uzbekistan

Keywords
Information Networks, Soft-Computing, Fuzzy Set Theory, Genetic Algorithms, Automated Control Systems
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 4 , Issue: 4 )
Date of Publication :
July 2014

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