DSpace@nitr >
National Institue of Technology- Rourkela >
Journal Articles >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/70

Title: Fuzzy neural network and fuzzy expert system for load forecasting
Authors: Dash, P K
Liew, A C
Rahman, S
Keywords: expert systems
fuzzy neural nets
load forecasting
Issue Date: Jan-1996
Publisher: IEE
Citation: IEE Proceedings-Generation, Transmission and Distribution, Vol 143, Iss 1, P 106-114
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, average, peak and hourly load forecasts
Description: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEE.
URI: http://hdl.handle.net/2080/70
Appears in Collections:Journal Articles

Files in This Item:

File Description SizeFormat
pkd13.pdf853KbAdobe PDFView/Open

Show full item record

All items in DSpace are protected by copyright, with all rights reserved.

 

Powered by DSpace Feedback