Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/16429
Title: An advanced evolutionary algorithm for parameter estimation of the discrete kalman filter
Authors: Chan, ZSH
Ngan, HW
Fung, YF
Rad, AB
Keywords: Adaptive mutation
Evolutionary algorithm
Genetic algorithm
Kalman filter
Load forecasting
Issue Date: 2001
Source: Computer physics communications, 2001, v. 142, no. 1-3, p. 248-254 How to cite?
Journal: Computer Physics Communications 
Abstract: In this work we design an advanced Evolutionary Algorithm (EA) for optimizing the discrete Kalman filter (KF) model. The EA employs parallel architecture and an advanced mutation operator called the "Selection Follower". Its performance is benchmarked with that of the Expectation-Maximization algorithm (EM) in minimizing the mean-square-error of the KF prediction. Experimental results show that the EA consistently outperforms the EM and runs significantly faster under the same number of function evaluations.
Description: Conference on Computational Physics (CCP'2000), Gold Coast, Qld., 3-8 December 2000
URI: http://hdl.handle.net/10397/16429
ISSN: 0010-4655
DOI: 10.1016/S0010-4655(01)00332-0
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