A novel genetic-algorithm-based neural network for short-term load forecasting

S. H. Ling, Hung Fat Frank Leung, H. K. Lam, Yim Shu Lee, Peter K S Tam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

99 Citations (Scopus)

Abstract

This paper presents a neural network with a novel neuron model. In this model, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. This neural network provides better performance than a traditional feedforward neural network, and fewer hidden nodes are needed. The parameters of the proposed neural network are tuned by a genetic algorithm with arithmetic crossover and nonuniform mutation. Some applications are given to show the merits of the proposed neural network.
Original languageEnglish
Pages (from-to)793-799
Number of pages7
JournalIEEE Transactions on Industrial Electronics
Volume50
Issue number4
DOIs
Publication statusPublished - 1 Aug 2003

Keywords

  • Genetic algorithm (GA)
  • Neural network
  • Short-term load forecasting

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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