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Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment

Genetic Algorithm (GA) belongs to elementary stochastic optimization algorithms inspired by evolution.It points out the ability of simple representations using bit strings to encode complicated structures and the power of simple transformations to reach the desired solution. Research shows that a ne...

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Main Authors: Fam, D.F., Koh, S.P., Tiong, S.K., Chong, K.H.
Format: Conference Paper
Language:en_US
Published: 2017
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spelling my.uniten.dspace-58132018-01-03T07:39:13Z Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment Fam, D.F. Koh, S.P. Tiong, S.K. Chong, K.H. Genetic Algorithm (GA) belongs to elementary stochastic optimization algorithms inspired by evolution.It points out the ability of simple representations using bit strings to encode complicated structures and the power of simple transformations to reach the desired solution. Research shows that a new operator namely Selective Clonal Mutation (SCM) for better genetic solutions has been successfully developed so that faster convergence to the best desired solution could be obtained. This operator has produced the best fitness value as compared to the conventional genetic algorithm result within 50 generation, Selective Clonal Mutation (SCM) is able to produce the best fitness value at 0.01731 with optimum voltage 10.05V in solar tracking environment. © (2012) Trans Tech Publications, Switzerland. 2017-12-08T07:26:23Z 2017-12-08T07:26:23Z 2012 Conference Paper 10.4028/www.scientific.net/AMR.341-342.456 en_US Advanced Materials Research Volume 341-342, 2012, Pages 456-461
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language en_US
description Genetic Algorithm (GA) belongs to elementary stochastic optimization algorithms inspired by evolution.It points out the ability of simple representations using bit strings to encode complicated structures and the power of simple transformations to reach the desired solution. Research shows that a new operator namely Selective Clonal Mutation (SCM) for better genetic solutions has been successfully developed so that faster convergence to the best desired solution could be obtained. This operator has produced the best fitness value as compared to the conventional genetic algorithm result within 50 generation, Selective Clonal Mutation (SCM) is able to produce the best fitness value at 0.01731 with optimum voltage 10.05V in solar tracking environment. © (2012) Trans Tech Publications, Switzerland.
format Conference Paper
author Fam, D.F.
Koh, S.P.
Tiong, S.K.
Chong, K.H.
spellingShingle Fam, D.F.
Koh, S.P.
Tiong, S.K.
Chong, K.H.
Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment
author_facet Fam, D.F.
Koh, S.P.
Tiong, S.K.
Chong, K.H.
author_sort Fam, D.F.
title Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment
title_short Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment
title_full Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment
title_fullStr Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment
title_full_unstemmed Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment
title_sort comparative analysis of selective clonal mutation with conventional ga operators in solar tracking environment
publishDate 2017
_version_ 1644493782383591424
score 13.222552

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