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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2011 IEEE Conference on Open Systems, ICOS 2011
Pages390-394
Number of pages5
DOIs
Publication statusPublished - 2011
Event2nd IEEE International Conference on Open Systems, ICOS 2011 - Langkawi, Malaysia
Duration: 25 Sep 201128 Sep 2011

Other

Other2nd IEEE International Conference on Open Systems, ICOS 2011
CountryMalaysia
CityLangkawi
Period25/09/1128/09/11

Fingerprint

Immune system
Gears

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software

Cite this

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title = "The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem",
abstract = "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.",
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Yaw, MW, Koh, JSP & Chong, KH 2011, The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem. in 2011 IEEE Conference on Open Systems, ICOS 2011., 6079307, pp. 390-394, 2nd IEEE International Conference on Open Systems, ICOS 2011, Langkawi, Malaysia, 25/09/11. https://doi.org/10.1109/ICOS.2011.6079307

The effect of mutation rate to artificial immune system algorithm optimization in solving engineering gear train problem. / Yaw, M. W.; Koh, Johnny Siaw Paw; Chong, Kok Hen.

2011 IEEE Conference on Open Systems, ICOS 2011. 2011. p. 390-394 6079307.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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