Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim

This project focuses on forecast of electricity consumption in Malaysia using artificial intelligence. From the world market, electricity consumption depends on the electrical usage of a bunch of society. Electricity consumption should correspond to the current demand because the production of exces...

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Main Author: Abd Rahim, Muhamad Farhan
Format: Thesis
Language:English
Published: 2013
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/84794/1/84794.pdf
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spelling my-uitm-ir.847942024-07-30T00:19:50Z Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim 2013 Abd Rahim, Muhamad Farhan Back propagation (Artificial intelligence) Neural networks (Computer science) This project focuses on forecast of electricity consumption in Malaysia using artificial intelligence. From the world market, electricity consumption depends on the electrical usage of a bunch of society. Electricity consumption should correspond to the current demand because the production of excess electricity and the reduction of electricity can cause economic loss. Almost of the large scale, it is impossible to do complete inspection because the time and cost increases drastically with increase in number of samples. This has created a need for a system that can inspect the components automatically with less cost and less time. The ANN will generate the pattern and predict the future pattern of electricity consumption. To improve the result of ANN model, the optimization method was used to optimize the forecast. As the result, the range of electricity consumption is obtained. 2013 Thesis https://ir.uitm.edu.my/id/eprint/84794/ https://ir.uitm.edu.my/id/eprint/84794/1/84794.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Johari, Dalina
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Johari, Dalina
topic Back propagation (Artificial intelligence)
Neural networks (Computer science)
spellingShingle Back propagation (Artificial intelligence)
Neural networks (Computer science)
Abd Rahim, Muhamad Farhan
Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim
description This project focuses on forecast of electricity consumption in Malaysia using artificial intelligence. From the world market, electricity consumption depends on the electrical usage of a bunch of society. Electricity consumption should correspond to the current demand because the production of excess electricity and the reduction of electricity can cause economic loss. Almost of the large scale, it is impossible to do complete inspection because the time and cost increases drastically with increase in number of samples. This has created a need for a system that can inspect the components automatically with less cost and less time. The ANN will generate the pattern and predict the future pattern of electricity consumption. To improve the result of ANN model, the optimization method was used to optimize the forecast. As the result, the range of electricity consumption is obtained.
format Thesis
qualification_level Bachelor degree
author Abd Rahim, Muhamad Farhan
author_facet Abd Rahim, Muhamad Farhan
author_sort Abd Rahim, Muhamad Farhan
title Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim
title_short Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim
title_full Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim
title_fullStr Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim
title_full_unstemmed Forecast electricity consumption in Malaysia using artificial intelligence / Muhamad Farhan Abd Rahim
title_sort forecast electricity consumption in malaysia using artificial intelligence / muhamad farhan abd rahim
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2013
url https://ir.uitm.edu.my/id/eprint/84794/1/84794.pdf
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