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Dual-head marking performance optimisation via evolutionary solutions

This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. The advantage of the 'self-evolving' nature of...

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Main Authors: Koh J., Tiong S.K., Aris I.B., Mahmoud S.
Other Authors: 22951210700
Format: Conference paper
Published: 2023
Subjects:
Computer programming
Database systems
Genetic algorithms
Knowledge acquisition
Optimization
Vectors
Marking speed
Molecular Marking Optimisation algorithm
Multi-head marking system
Optimised marking performance
Marking machines
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id my.uniten.dspace-29740
record_format dspace
spelling my.uniten.dspace-297402023-12-28T16:08:40Z Dual-head marking performance optimisation via evolutionary solutions Koh J. Tiong S.K. Aris I.B. Mahmoud S. 22951210700 15128307800 6603306751 7202300402 Computer programming Database systems Genetic algorithms Knowledge acquisition Optimization Vectors Marking speed Molecular Marking Optimisation algorithm Multi-head marking system Optimised marking performance Marking machines This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. The advantage of the 'self-evolving' nature of the Genetic Algorithm has been considered to discover the most relevant combination of features for each diagnosis considered. The knowledge acquired by the process is interpreted and mapped into vectors, which are kept in the database and used by the system to guide its reasoning process. The representation approach has been implemented via computer program in order to achieve optimised marking performance. Also, the performance of the new operators for evolutionary approaches to the time-based problem has been discussed in the paper. � 2005 IEEE. Final 2023-12-28T08:08:40Z 2023-12-28T08:08:40Z 2006 Conference paper 10.1109/DELTA.2006.39 2-s2.0-33847113940 https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847113940&doi=10.1109%2fDELTA.2006.39&partnerID=40&md5=7b75dcb26dccbd26e3e53b61fd4d6a3c https://irepository.uniten.edu.my/handle/123456789/29740 2006 1581192 85 88 Scopus
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/
topic Computer programming
Database systems
Genetic algorithms
Knowledge acquisition
Optimization
Vectors
Marking speed
Molecular Marking Optimisation algorithm
Multi-head marking system
Optimised marking performance
Marking machines
spellingShingle Computer programming
Database systems
Genetic algorithms
Knowledge acquisition
Optimization
Vectors
Marking speed
Molecular Marking Optimisation algorithm
Multi-head marking system
Optimised marking performance
Marking machines
Koh J.
Tiong S.K.
Aris I.B.
Mahmoud S.
Dual-head marking performance optimisation via evolutionary solutions
description This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. The advantage of the 'self-evolving' nature of the Genetic Algorithm has been considered to discover the most relevant combination of features for each diagnosis considered. The knowledge acquired by the process is interpreted and mapped into vectors, which are kept in the database and used by the system to guide its reasoning process. The representation approach has been implemented via computer program in order to achieve optimised marking performance. Also, the performance of the new operators for evolutionary approaches to the time-based problem has been discussed in the paper. � 2005 IEEE.
author2 22951210700
author_facet 22951210700
Koh J.
Tiong S.K.
Aris I.B.
Mahmoud S.
format Conference paper
author Koh J.
Tiong S.K.
Aris I.B.
Mahmoud S.
author_sort Koh J.
title Dual-head marking performance optimisation via evolutionary solutions
title_short Dual-head marking performance optimisation via evolutionary solutions
title_full Dual-head marking performance optimisation via evolutionary solutions
title_fullStr Dual-head marking performance optimisation via evolutionary solutions
title_full_unstemmed Dual-head marking performance optimisation via evolutionary solutions
title_sort dual-head marking performance optimisation via evolutionary solutions
publishDate 2023
_version_ 1806428241950408704
score 13.222552

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