Research of Enhancing Smooth Degree of data sequence Based on Genetic Algorithm and Its Application

Author

Junfeng Li ; Yang, Aiping ; Dai, Wenzhan ; Junfeng Li

Author_Institution

Zhejiang Sci-Tech Univ., Hangzhou

fYear

2007

fDate

18-21 Aug. 2007

Firstpage

2133

Lastpage

2137

Abstract

In this paper, the methods of enhancing smooth degree of original data sequence by means of function transformation are studied and the method of power function x^-a (a > 0) transformation against modeling data is put forward. Moreover, the shortages of function transformation are pointed out when the parameters of the function transformation are selected and the realization methods of function transformation based on GA are given. The method can widen range of application of grey model. At last, the model of Chinese country per-capita housing areas is built by means of the method and the model´s precision is 99%. The example of application shows the effectiveness of the proposed approach.

Keywords

genetic algorithms; grey systems; Chinese country per-capita housing areas; function transformation; genetic algorithm; grey model; original data sequence; power function transformation; smooth degree enhancement; Automation; Cities and towns; Educational institutions; Finance; Forward contracts; Genetic algorithms; Genetic mutations; Logistics; Mechanical engineering; Predictive models; GM(1,1); Genetic algorithm; Grey system theory; Smooth degree;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2007 IEEE International Conference on

Conference_Location

Jinan

Print_ISBN

978-1-4244-1531-1

Type

conf

DOI

10.1109/ICAL.2007.4338928

Filename

4338928