An advanced evolutionary algorithm for load forecasting with the kalman filter

被引：0

作者：

Chan, ZSH ^{[1
]}

Ngan, HW ^{[1
]}

Fung, YF ^{[1
]}

Rad, AB ^{[1
]}

机构：

[1] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China

来源：

APSCOM - 2000: 5TH INTERNATIONAL CONFERENCE ON ADVANCES IN POWER SYSTEM CONTROL, OPERATION & MANAGEMENT, VOLS 1 AND 2 | 2000年

关键词：

evolutionary algorithm; genetic algorithm; Kalman filter; adaptive mutation; load forecasting;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this work we design an advanced Evolutionary Algorithm for optimizing a Kalman Filter 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 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.

引用

页码：134 / 138

页数：3

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