Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/62236
Title: Fuzzy neural network and fuzzy expert system for load forecasting
Authors: Dash, P.K.
Liew, A.C. 
Rahman, S.
Keywords: Expert systems
Load forecasting
Neural networks
Power system planning
Issue Date: 1996
Source: Dash, P.K.,Liew, A.C.,Rahman, S. (1996). Fuzzy neural network and fuzzy expert system for load forecasting. IEE Proceedings: Generation, Transmission and Distribution 143 (1) : 106-114. ScholarBank@NUS Repository.
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. © IEE, 1996.
Source Title: IEE Proceedings: Generation, Transmission and Distribution
URI: http://scholarbank.nus.edu.sg/handle/10635/62236
ISSN: 13502360
Appears in Collections:Staff Publications

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