Adaptive genetic algorithms used to analyze behavior of complex system

被引：32

作者：

Mokshin, Anatolii, V ^{[1
]}

Mokshin, Vladimir V. ^{[2
,3
]}

Sharnin, Leonid M. ^{[2
]}

机构：

[1] Kazan Fed Univ, Inst Phys, Kazan 420008, Russia

[2] Kazan Natl Res Tech Univ, Inst Comp Technol & Informat Protect, Kai 420111, Kasan, Russia

[3] Kazan Natl Res Tech Univ, Automat & Control Syst Lab, Siemens Engn Ctr, Kai 420111, Kasan, Russia

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2019年 / 71卷

关键词：

Complex systems; Factors selection; Genetic algorithm; Regression model; Correlation analysis; COMMUNITY DETECTION;

D O I：

10.1016/j.cnsns.2018.11.014

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

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.

引用

页码：174 / 186

页数：13

共 34 条

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