Research and Application of Multiple Regression Analysis Based on Genetic Algorithm

被引：0

作者：

Tang Chan-yi ^{[1
]}

Lin Man-shan ^{[1
]}

机构：

[1] N China Univ Technol, Informat Engn Coll, Beijing 100041, Peoples R China

来源：

ITESS: 2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES, PT 2 | 2008年

关键词：

Genetic Algorithm; Multiple Regression; Reproduction; Crossover; Mutation; Evaluation Function;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper deals with parameters selection of multiple regression analysis by genetic algorithm. Though analyzing which parameters having relations with the output of aluminum in the aluminium electrolytic industry, we constructed multiple regression models. We used binary code for individual who is in the solution space, selected individual by fitness ratio, then reproduction, crossover and mutation for the population. With a large number of iterative, we got the approximate solution of equation's coefficients. The experimental results indicate that using genetic algorithms to solve the multiple regression equation coefficients with high precision and intelligent. This model is suitable for forecasting, and can be used to guide practice.

引用

页码：256 / 261

页数：6

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