Parameter estimation of rational models based on artificial bee colony algorithm

Author

Wu, Defeng ; Yu, Wanneng ; Yin, Zibin

Author_Institution

Sch. of Marine Eng., Jimei Univ., Xiamen, China

fYear

2011

fDate

26-29 June 2011

Firstpage

219

Lastpage

224

Abstract

Artificial bee colony (ABC) algorithm is a simple, robust and population based stochastic optimization algorithm based on a particular intelligent behavior of honeybee swarms. Non-linear rational model has been one of the most popular non-linear autoregressive moving average with exogenous input (NARMAX) sub-model sets. In this study, an approach based on artificial bee colony algorithm for estimating the parameters of non-linear rational models is presented. The effectiveness of the ABCE algorithm is initially demonstrated by some simulation experiments.

Keywords

autoregressive moving average processes; nonlinear programming; parameter estimation; stochastic programming; NARMAX; artificial bee colony algorithm; exogenous input submodel sets; honeybee swarms; intelligent behavior; nonlinear autoregressive moving average; nonlinear rational model; parameter estimation; population based stochastic optimization algorithm; Autoregressive processes; Computational modeling; Mathematical model; Optimization; Parameter estimation; Polynomials; Prediction algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Modelling, Identification and Control (ICMIC), Proceedings of 2011 International Conference on

Conference_Location

Shanghai

Type

conf

DOI

10.1109/ICMIC.2011.5973704

Filename

5973704