Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari

This project presents the development of hybrid evolutionary programming (EP) and artificial neural network (ANN) prediction system for lightning occurrence based on historical lightning and meteorological data from a Malaysian environment. It involved the development of ANN design and embedding EP...

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Main Author:	Johari, Dalina
Format:	Thesis
Language:	English
Published:	2009
Subjects:	Instruments and machines Control engineering systems. Automatic machinery (General)
Online Access:	http://ir.uitm.edu.my/id/eprint/27273/ http://ir.uitm.edu.my/id/eprint/27273/1/TM_DALINA%20JOHARI%20EE%2009_5.pdf

id	uitm-27273
recordtype	eprints
spelling	uitm-272732020-01-14T08:59:10Z http://ir.uitm.edu.my/id/eprint/27273/ Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari Johari, Dalina Instruments and machines Control engineering systems. Automatic machinery (General) This project presents the development of hybrid evolutionary programming (EP) and artificial neural network (ANN) prediction system for lightning occurrence based on historical lightning and meteorological data from a Malaysian environment. It involved the development of ANN design and embedding EP optimization technique for optimizing selected ANN parameters in order to improve the system's generalization capability.ANN, an intelligent machine learning technique, is inspired by the way our biological nervous systems process information. With the ability to learn by example and do tasks based on training experience, it is profoundly suitable for pattern recognition and forecasting tasks. Due to ANN heuristics nature, though, the process of finding suitable network architectures could be arduous and time-consuming. It highly depends on expert experience and is a tedious trial and error process. There is also no systematic way to design the optimal architecture for a given task automatically. For that reason, an efficient optimization technique such as EP was employed in the study to find the best ANN architectures systematically and perform lightning prediction accurately with less computation time. Comparative study conducted between determining ANN parameters heuristically and by using EP revealed that hybrid EP optimization technique with the ANN produced better results for the ANN in terms of its R-value and computational time. The most significant advantage of using EP optimization technique is that it provides a structured and automatic way for obtaining optimal values of the ANN parameters, while using heuristic technique, each possible value had to be tried one by one manually before the optimal values could be found. As a result, the developed lightning prediction system is able to generalize well when presented with new sets of input data. Consequently, prediction of the lightning occurrence can be successfully done. 2009 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/27273/1/TM_DALINA%20JOHARI%20EE%2009_5.pdf Johari, Dalina (2009) Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari. Masters thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Instruments and machines Control engineering systems. Automatic machinery (General)
spellingShingle	Instruments and machines Control engineering systems. Automatic machinery (General) Johari, Dalina Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari
description	This project presents the development of hybrid evolutionary programming (EP) and artificial neural network (ANN) prediction system for lightning occurrence based on historical lightning and meteorological data from a Malaysian environment. It involved the development of ANN design and embedding EP optimization technique for optimizing selected ANN parameters in order to improve the system's generalization capability.ANN, an intelligent machine learning technique, is inspired by the way our biological nervous systems process information. With the ability to learn by example and do tasks based on training experience, it is profoundly suitable for pattern recognition and forecasting tasks. Due to ANN heuristics nature, though, the process of finding suitable network architectures could be arduous and time-consuming. It highly depends on expert experience and is a tedious trial and error process. There is also no systematic way to design the optimal architecture for a given task automatically. For that reason, an efficient optimization technique such as EP was employed in the study to find the best ANN architectures systematically and perform lightning prediction accurately with less computation time. Comparative study conducted between determining ANN parameters heuristically and by using EP revealed that hybrid EP optimization technique with the ANN produced better results for the ANN in terms of its R-value and computational time. The most significant advantage of using EP optimization technique is that it provides a structured and automatic way for obtaining optimal values of the ANN parameters, while using heuristic technique, each possible value had to be tried one by one manually before the optimal values could be found. As a result, the developed lightning prediction system is able to generalize well when presented with new sets of input data. Consequently, prediction of the lightning occurrence can be successfully done.
format	Thesis
author	Johari, Dalina
author_facet	Johari, Dalina
author_sort	Johari, Dalina
title	Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari
title_short	Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari
title_full	Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari
title_fullStr	Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari
title_full_unstemmed	Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari
title_sort	hybrid evolutionary programming-artificial neural network-based lightning prediction system / dalina johari
publishDate	2009
url	http://ir.uitm.edu.my/id/eprint/27273/ http://ir.uitm.edu.my/id/eprint/27273/1/TM_DALINA%20JOHARI%20EE%2009_5.pdf
first_indexed	2023-09-18T23:18:09Z
last_indexed	2023-09-18T23:18:09Z
_version_	1777419251460603904

Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari

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