Optimal prediction model using improved differential evolution algorithm

Author

Zheng, Ming-Chang ; Chou, Jyh-Horng ; Chen, Shinn-Horng

Author_Institution

Inst. of Eng. Sci. & Technol., Nat. Kaohsiung First Univ. of Sci. & Technol., Kaohsiung, Taiwan

Volume

3

fYear

2011

fDate

10-13 July 2011

Firstpage

1409

Lastpage

1413

Abstract

A Taguchi-based the differential evolution (TDE) is applied as an improved the differential evolution to solve the global optimization. The differential evolution (DE) is an easy and valid evolutionary algorithm for fitness function optimization. For grey forecasting model (GM) which is a time series forecasting model, the parameters are calculated by the TDE. The academic research of Wang and Hsu is a base of this paper. Finally, the forecasted result of TDEGM is superior to other evolutionary algorithms.

Keywords

differential equations; evolutionary computation; forecasting theory; optimisation; time series; Taguchi-based differential evolution; academic research; evolutionary algorithm; fitness function optimization; global optimization; grey forecasting model; improved differential evolution algorithm; optimal prediction model; time series forecasting model; Cybernetics; Forecasting; Genetic algorithms; Integrated circuit modeling; Machine learning; Mathematical model; Predictive models; Evolution algorithm; Grey forecasting model; Optimal;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics (ICMLC), 2011 International Conference on

Conference_Location

Guilin

ISSN

2160-133X

Print_ISBN

978-1-4577-0305-8

Type

conf

DOI

10.1109/ICMLC.2011.6016882

Filename

6016882