Tatiana Karaseva
Eugene Semenkin
Department of System Analysis and Operations Research, Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science, Krasnoyarsk
Department of Business Informatics and Business Process Modeling, Institute of Business Process Management, Siberian Federal University, Krasnoyarsk
Russian Federation
e-mail: tatyanakarasewa@yandex.ru
Abstract:
Evolutionary algorithms are effective tools for solving different problems such as mathematical modelling. The paper proposes an evolutionary approach to the identification of dynamic systems. It combines a genetic programming algorithm and a differential evolution method. The main modifications of the evolutionary steps for these algorithms are presented. The investigation and testing of the proposed approach was performed on problems of various dimensions.
Key words:
Hybrid evolutionary approach
Genetic programming
Differential evolution
Self-configuration
Identification