Genetic-based multi-layered perceptrons for Taiwan power system short term load forecasting

Shyh Jier Huang, Ching Lien Huang

Research output: Contribution to conferencePaperpeer-review

Abstract

A new approach of using genetic algorithms based multi-layered perceptrons (GA-MLP) to solve short term load forecasting problems is proposed in this paper. Merits of genetic algorithms are included to prevent the learning stagnation in the neural network learning process. The proposed method is tested on the load data from Taiwan Power Company. The results demonstrate the feasibility of the proposed approach to applications.

Original languageEnglish
Pages785-790
Number of pages6
Publication statusPublished - 1995 Dec 1
EventProceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95 - St.Louis, MO, USA
Duration: 1995 Nov 121995 Nov 15

Other

OtherProceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95
CitySt.Louis, MO, USA
Period95-11-1295-11-15

All Science Journal Classification (ASJC) codes

  • Software

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