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NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY

Neural networks for the real world applications are increasing rapidly. Artificial Neural Network is a system loosely modeled based on the human brain. It has ability to account for any functional dependency. The network discovers by learning and modeling the nature of the dependency without need...

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Main Author: ZAHARULHISHAM, NURUL HAMIZA
Format: Final Year Project
Language:English
Published: Universiti Teknologi Petronas 2011
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://utpedia.utp.edu.my/8253/1/2011%20-%20Neural%20network%20prediction%20model%20of%20energy%20consumption%20for%20billing%20integrity.pdf
http://utpedia.utp.edu.my/8253/
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spelling my-utp-utpedia.82532017-01-25T09:42:28Z http://utpedia.utp.edu.my/8253/ NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY ZAHARULHISHAM, NURUL HAMIZA TK Electrical engineering. Electronics Nuclear engineering Neural networks for the real world applications are increasing rapidly. Artificial Neural Network is a system loosely modeled based on the human brain. It has ability to account for any functional dependency. The network discovers by learning and modeling the nature of the dependency without needing to be prompted. Nowadays, neural networks are a powerful technique to solve many real world problems. They have the ability to learn from experience in order to improve their performance and to adapt themselves to the changes in the environment. Furthermore, they are able to deal with incomplete information or noisy data and can be very effective especially in situations where it is not possible to define the rules or steps that lead to the solution of a problem. This report contains five chapters which are the introduction, literature review methodology, results and discussions and the conclusion. In the first chapter, the introduction explains about the background study, problem statement and also the main objectives of the project. The main objective of the project is to develop a neural network model to predict energy consumption for billing integrity. The second chapter of this report stated the theory and literature review of the neural network. The literature review is taken mostly from journals of many previous studies about neural network. Next, the third chapter explains about the methodology of the project. Under the methodology section, the author includes a project activities flow chart and also explains about the tools required to execute the project. This project is carried out in two semesters. The milestone for the project work is presented nicely in a Gantt chart. Then, in the results and discnssion chapter, the author stated about the neural network model developed using ¥-ATLAB. Last but not least, the conclusion recommendations for the model im11rovement. Universiti Teknologi Petronas 2011-05 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/8253/1/2011%20-%20Neural%20network%20prediction%20model%20of%20energy%20consumption%20for%20billing%20integrity.pdf ZAHARULHISHAM, NURUL HAMIZA (2011) NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY. Universiti Teknologi Petronas. (Unpublished)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
ZAHARULHISHAM, NURUL HAMIZA
NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY
description Neural networks for the real world applications are increasing rapidly. Artificial Neural Network is a system loosely modeled based on the human brain. It has ability to account for any functional dependency. The network discovers by learning and modeling the nature of the dependency without needing to be prompted. Nowadays, neural networks are a powerful technique to solve many real world problems. They have the ability to learn from experience in order to improve their performance and to adapt themselves to the changes in the environment. Furthermore, they are able to deal with incomplete information or noisy data and can be very effective especially in situations where it is not possible to define the rules or steps that lead to the solution of a problem. This report contains five chapters which are the introduction, literature review methodology, results and discussions and the conclusion. In the first chapter, the introduction explains about the background study, problem statement and also the main objectives of the project. The main objective of the project is to develop a neural network model to predict energy consumption for billing integrity. The second chapter of this report stated the theory and literature review of the neural network. The literature review is taken mostly from journals of many previous studies about neural network. Next, the third chapter explains about the methodology of the project. Under the methodology section, the author includes a project activities flow chart and also explains about the tools required to execute the project. This project is carried out in two semesters. The milestone for the project work is presented nicely in a Gantt chart. Then, in the results and discnssion chapter, the author stated about the neural network model developed using ¥-ATLAB. Last but not least, the conclusion recommendations for the model im11rovement.
format Final Year Project
author ZAHARULHISHAM, NURUL HAMIZA
author_facet ZAHARULHISHAM, NURUL HAMIZA
author_sort ZAHARULHISHAM, NURUL HAMIZA
title NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY
title_short NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY
title_full NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY
title_fullStr NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY
title_full_unstemmed NEURAL NETWORK PREDICTION MODEL OF ENERGY CONSUMPTION FOR BILLING INTEGRITY
title_sort neural network prediction model of energy consumption for billing integrity
publisher Universiti Teknologi Petronas
publishDate 2011
url http://utpedia.utp.edu.my/8253/1/2011%20-%20Neural%20network%20prediction%20model%20of%20energy%20consumption%20for%20billing%20integrity.pdf
http://utpedia.utp.edu.my/8253/
_version_ 1739831556043702272
score 13.211869

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