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The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem

Artificial Immune System (AIS) algorithm has a great interest for the researcher recently because AIS have a big room for improvement since AIS does not have a fix algorithm template. This paper analyzes the effect of impact of mutation rate compare to the standard AIS algorithm. The purpose of this...

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Main Authors: Yaw, M.W., Koh, S.P., Chong, K.H.
Format: Conference Paper
Language:en_US
Published: 2017
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spelling my.uniten.dspace-58152018-01-03T07:46:10Z The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem Yaw, M.W. Koh, S.P. Chong, K.H. Artificial Immune System (AIS) algorithm has a great interest for the researcher recently because AIS have a big room for improvement since AIS does not have a fix algorithm template. This paper analyzes the effect of impact of mutation rate compare to the standard AIS algorithm. The purpose of this stimulation was done is to understand deeply the affected step in the standard AIS algorithm. It can increase the efficiency to obtain the final best solution for the particular solving problem. By comparing the optimization result in the Gear Train using Evolutionary [1], HAIS [2], GeneAS [3] and GPSO [4], it is observed that changing the mutation rate on standard AIS algorithm can achieve a better solution. © 2011 IEEE. 2017-12-08T07:26:24Z 2017-12-08T07:26:24Z 2011 Conference Paper 10.1109/ICOS.2011.6079307 en_US 2011 IEEE Conference on Open Systems, ICOS 2011 2011, Article number 6079307, Pages 390-394
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 Artificial Immune System (AIS) algorithm has a great interest for the researcher recently because AIS have a big room for improvement since AIS does not have a fix algorithm template. This paper analyzes the effect of impact of mutation rate compare to the standard AIS algorithm. The purpose of this stimulation was done is to understand deeply the affected step in the standard AIS algorithm. It can increase the efficiency to obtain the final best solution for the particular solving problem. By comparing the optimization result in the Gear Train using Evolutionary [1], HAIS [2], GeneAS [3] and GPSO [4], it is observed that changing the mutation rate on standard AIS algorithm can achieve a better solution. © 2011 IEEE.
format Conference Paper
author Yaw, M.W.
Koh, S.P.
Chong, K.H.
spellingShingle Yaw, M.W.
Koh, S.P.
Chong, K.H.
The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem
author_facet Yaw, M.W.
Koh, S.P.
Chong, K.H.
author_sort Yaw, M.W.
title The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem
title_short The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem
title_full The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem
title_fullStr The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem
title_full_unstemmed The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem
title_sort effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem
publishDate 2017
_version_ 1644493782989668352
score 13.214268

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