Research of Improved GM(1,1) Model Based on Particle Swarm

Author

Li Jing ; Mu Xiao-dong ; Shi Ling ; Xiong Bin

Author_Institution

Xian Res. Inst. of Hi-Tech Hongqing Town, Xian

fYear

2009

fDate

22-24 Jan. 2009

Firstpage

444

Lastpage

447

Abstract

Grey theory has been applied widely in the field of prediction and decision, but model precision is influenced extremely by sequence smooth degree, boundary value and background value. Particle swarm has well effect in searching for best result because it is an efficient way. The paper advances a new method, improved particle swarm is used to optimize the boundary value and background value of GM(1,1) model, and sin function is used to deal with sequence. It has been shown that the improved model is better through predicting the lifetime of mechanical products.

Keywords

boundary-value problems; grey systems; mechanical products; operations research; particle swarm optimisation; reliability theory; remaining life assessment; boundary value problem; grey theory; model precision; particle swarm; sequence smooth degree; sin function; Accuracy; Biochemistry; Cities and towns; Mechanical products; Optimization methods; Particle swarm optimization; Prediction algorithms; Predictive models; 1) Model; Background Value; Boundary Value; Metabolism GM(1; Particle Swarm;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computer Control, 2009. ICACC '09. International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-3330-8

Type

conf

DOI

10.1109/ICACC.2009.63

Filename

4777382