Genetic-based multilayered perceptron for Taiwan power system short-term load forecasting

Shyh Jier Huang, Ching Lien Huang

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

A new approach using a genetic algorithm based multilayered perceptron (GA-MLP) to solve short-term load forecasting problems is proposed in this paper. The merit of genetic algorithms is that they prevent 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 for applications.

Original languageEnglish
Pages (from-to)69-74
Number of pages6
JournalElectric Power Systems Research
Volume38
Issue number1
DOIs
Publication statusPublished - 1996 Jul 1

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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