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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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第一著者: Hassan, Elia Erwani
フォーマット: 学位論文
言語:English
出版事項: 1998
オンライン･アクセス:https://ir.uitm.edu.my/id/eprint/101732/1/101732.pdf
https://ir.uitm.edu.my/id/eprint/101732/
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id my.uitm.ir.101732
record_format eprints
spelling my.uitm.ir.1017322024-09-14T07:19:48Z https://ir.uitm.edu.my/id/eprint/101732/ An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan 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 NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/101732/1/101732.pdf An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan. (1998) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
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
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
publishDate 1998
url https://ir.uitm.edu.my/id/eprint/101732/1/101732.pdf
https://ir.uitm.edu.my/id/eprint/101732/
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score 13.251813

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