An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan

This study is covered a new approach to load forecasting using Artificial Neural Network (ANNs). Improving accuracy of load forecast by Back Propagation Algorithm is the main objective for this project. This accuracy is dependent on several ANN parameters such as learning rate and momentum rate. The...

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Bibliographic Details
Main Author:	Hassan, Elia Erwani
Format:	Thesis
Language:	English
Published:	1998
Online Access:	https://ir.uitm.edu.my/id/eprint/101732/1/101732.pdf
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id	my-uitm-ir.101732
record_format	uketd_dc
spelling	my-uitm-ir.1017322024-09-14T07:19:48Z An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan 1998 Hassan, Elia Erwani This study is covered a new approach to load forecasting using Artificial Neural Network (ANNs). Improving accuracy of load forecast by Back Propagation Algorithm is the main objective for this project. This accuracy is dependent on several ANN parameters such as learning rate and momentum rate. The Back Propagation Algorithm, which consists of the multi-layered perception model, makes possible to train the ANN training pattems. As an input, we look at the past 24 hours load data with the type of days as weekdays, Sunday and public holidays. The next 24 hours load patters are considered as outputs. By using Back Propagation Algorithm with 25 hidden nodes, 0.7 learning rate and 0.7 momentum rate have been found to give faster result than other conventional techniques. 1998 Thesis https://ir.uitm.edu.my/id/eprint/101732/ https://ir.uitm.edu.my/id/eprint/101732/1/101732.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty Of Electrical Engineering
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
description	This study is covered a new approach to load forecasting using Artificial Neural Network (ANNs). Improving accuracy of load forecast by Back Propagation Algorithm is the main objective for this project. This accuracy is dependent on several ANN parameters such as learning rate and momentum rate. The Back Propagation Algorithm, which consists of the multi-layered perception model, makes possible to train the ANN training pattems. As an input, we look at the past 24 hours load data with the type of days as weekdays, Sunday and public holidays. The next 24 hours load patters are considered as outputs. By using Back Propagation Algorithm with 25 hidden nodes, 0.7 learning rate and 0.7 momentum rate have been found to give faster result than other conventional techniques.
format	Thesis
qualification_level	Bachelor degree
author	Hassan, Elia Erwani
spellingShingle	Hassan, Elia Erwani An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
author_facet	Hassan, Elia Erwani
author_sort	Hassan, Elia Erwani
title	An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
title_short	An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
title_full	An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
title_fullStr	An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
title_full_unstemmed	An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
title_sort	application of artificial neural network on short term load forecasting using back propagation algorithm / elia erwani hassan
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty Of Electrical Engineering
publishDate	1998
url	https://ir.uitm.edu.my/id/eprint/101732/1/101732.pdf
_version_	1811769188161683456

An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan

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