Please use this identifier to cite or link to this item:
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
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.
ISBN: 0-85296-791-8
DOI: 10.1049/cp:20000379
Appears in Collections:Conference Paper

View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

Last Week
Last month
Citations as of Aug 14, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.