Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37808
Title: An advanced evolutionary algorithm for load forecasting with the Kalman filter
Authors: Chan, ZSH
Ngan, HW 
Fung, YF
Rad, AB
Keywords: Kalman filters
Evolutionary computation
Filtering theory
Load forecasting
Optimisation
Power systems
Issue Date: 2000
Source: Fifth International Conference on Advances in Power System Control, Operation and Management : APSCOM-00 : October 30-November 1, 2000, Sheraton Hong Kong Hotel, p. 134-138 How to cite?
Abstract: In this work, the authors design an advanced evolutionary algorithm for optimizing a Kalman filter (KF) load forecasting 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 (EM) algorithm in minimizing the mean-square-error of the KF prediction. Results show that although the EA requires more function evaluations, it outperforms the EM algorithm consistently.
URI: http://hdl.handle.net/10397/37808
ISBN: 0-85296-791-8
DOI: 10.1049/cp:20000379
Appears in Collections:Conference Paper

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