Study on an Intelligent Forecast Algorithm and its Using in Complex System

Author

Fang, Jiandong ; Zhao, Yudong

Author_Institution

Inner Mongolia Univ. of Technol., Huhhot

fYear

2008

fDate

1-3 Nov. 2008

Firstpage

85

Lastpage

88

Abstract

According to specificity of the complex system process with stochastic uncertainty and correlation, a kind of predictive method based on gray system theories is presented. A nonlinear and multi-variable predictive model approach is established by the Taylor series expansion extended the single deformation prediction model in order to estimate more. The effectiveness of the model is confirmed through a computational experience, and the feasibility of the solutions is stipulated at the same time. Thus this predictive control strategy introduces a new way for generic nonlinear control.

Keywords

agriculture; large-scale systems; multivariable control systems; nonlinear control systems; predictive control; Taylor series expansion; complex system; deformation prediction model; generic nonlinear control; gray system theories; intelligent forecast algorithm; multi-variable predictive model approach; nonlinear predictive model approach; predictive method; stochastic uncertainty; Condition monitoring; Economic forecasting; Intelligent networks; Intelligent systems; Predictive models; Production; Stochastic systems; Taylor series; Technology forecasting; Uncertainty; complex system; extend information; precision control;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3391-9

Electronic_ISBN

978-0-7695-3391-9

Type

conf

DOI

10.1109/ICINIS.2008.97

Filename

4683174