A New Short Term Electrical Load Forecasting by Type-2 Fuzzy Neural Networks

A New Short Term Electrical Load Forecasting by Type-2 Fuzzy Neural Networks

In this study, we present a new approach for load forecasting (LF) using a recurrent fuzzy neural network (RFNN) for Kermanshah City. Imagine if there is a need for electricity in a region in the coming years, we will have to build a power plant or reinforce transmission lines, so this will be resol...

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Bibliographic Details
Main Authors:	Alanazi, A. (Author), Alattas, K. (Author), El-Sousy, F. (Author), Mobayen, S. (Author), Mohammadzadeh, A. (Author), Skruch, P. (Author), Tavoosi, J. (Author), Tian, M.-W (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Electric load forecasting Electric power plant loads Electrical load electrical load forecasting Electrical load forecasting Fuzzy inference Fuzzy neural networks Fuzzy-neural-networks Load forecasting machine learning New approaches recurrent fuzzy neural network Recurrent fuzzy neural network Recurrent neural networks Short-term electrical loads time series Times series Transmission-line Type-2 fuzzy
Online Access:	View Fulltext in Publisher

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