Fuzzy neural network and fuzzy expert system for load forecasting
- 1 January 1996
- journal article
- Published by Institution of Engineering and Technology (IET) in IEE Proceedings - Generation, Transmission and Distribution
- Vol. 143 (1), 106-114
- https://doi.org/10.1049/ip-gtd:19960314
Abstract
A hybrid neural network fuzzy expert system is developed to forecast short-term electric load accurately. The fuzzy membership values of the load and other weather variables are the inputs to the neural network, and the output comprises the membership values of the predicted load. An adaptive fuzzy correction scheme is used to forecast the final load by using a fuzzy rule base and fuzzy inference mechanism. Extensive studies have been performed for all seasons, and a few examples are presented in the paper, including average, peak and hourly load forecasts.Keywords
This publication has 3 references indexed in Scilit:
- Recurrent neural networks and load forecastingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A study on neural networks for short-term load forecastingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Short term electric load forecasting using an adaptively trained layered perceptronPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002