Journal
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
Volume 71, Issue -, Pages 174-186Publisher
ELSEVIER
DOI: 10.1016/j.cnsns.2018.11.014
Keywords
Complex systems; Factors selection; Genetic algorithm; Regression model; Correlation analysis
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Funding
- RFBR [18-02-00407]
- Ministry of Education and Science [3.2166.2017/4.6]
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In the present study, we consider a complex system whose behavior is characterized by set of various time-dependent factors. Some of these factors can characterize the external influences on the system, whereas other factors contain information generated by system. We demonstrate that time-dependence of these factors can be reproduced by the nonlinear regression model. The concrete form of this regression model is constructed on the basis of the genetic algorithms technique. This allows us to predict a possible behavior of the system and to identify the so-called significant factors that have a significant impact on the behavior of the system. To demonstrate validity of the method, we apply it to analyze the data characterizing a manufacturing company and the meteorological data. (C) 2018 Elsevier B.V. All rights reserved.
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