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Author Aly, W.M. ♦ Sheta, A.F. ♦ Abdelaziz, A.R.
Sponsorship Arab Comput. Soc. ♦ IEEE Comput. Soc
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2003
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Load modeling ♦ Power system modeling ♦ Power generation ♦ Load forecasting ♦ Genetic programming ♦ Predictive models ♦ Electrical engineering ♦ Computer science ♦ Artificial intelligence ♦ Evolutionary computation
Abstract Summary form only given. Load forecasting has become one of the major research areas in electrical engineering and computer science. Many of the traditional forecasting and artificial intelligent techniques are explored. We introduce evolutionary computation as a tool for developing new model structures to forecast power plant loads. We are exploring the use of genetic programming (GP) as a tool to build various model structures for electricity load forecasting. The developed GP models consider long-term load forecasting. The models are developed using real-measurements taken from commercial, domestic, farming, industrial and public lightning applications. The developed GP model results are very promising compared to traditional model structures.
Description Author affiliation: Electr. Eng. Dept., Alexandria Univ., Egypt (Aly, W.M.)
ISBN 0780379837
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2003-07-14
Publisher Place Tunisia
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 30.51 kB


Source: IEEE Xplore Digital Library