Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming

The emergence of 3-Satisfiability (3-SAT) problem has produced a prolific number of works devoted to the field of logic and data mining. In this study, a new hybrid method in doing logic programming by incorporating 3-SAT logical rules as a computational tool will be presented. Hence, a robust intel...

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Main Author:	Mansor, Mohd. Asyraf
Format:	Thesis
Language:	English
Published:	2017
Subjects:	QA1-939 Mathematics
Online Access:	http://eprints.usm.my/45423/1/MOHD.%20ASYRAF%20MANSOR.pdf
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id	my-usm-ep.45423
record_format	uketd_dc
spelling	my-usm-ep.454232019-09-17T01:54:07Z Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming 2017-08 Mansor, Mohd. Asyraf QA1-939 Mathematics The emergence of 3-Satisfiability (3-SAT) problem has produced a prolific number of works devoted to the field of logic and data mining. In this study, a new hybrid method in doing logic programming by incorporating 3-SAT logical rules as a computational tool will be presented. Hence, a robust intelligence system that integrates the Hopfield neural network and metaheuristic paradigm is constructed to extract the data set hidden knowledge in the form of 3-Satisfiability logical rule. A hybrid network called HNN-3SATAIS is proposed by assimilating the Hopfield neural network with the enhanced artificial immune system (AIS) algorithm as a training tool in doing 3-Satisfiability logic programming. 2017-08 Thesis http://eprints.usm.my/45423/ http://eprints.usm.my/45423/1/MOHD.%20ASYRAF%20MANSOR.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Matematik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA1-939 Mathematics
spellingShingle	QA1-939 Mathematics Mansor, Mohd. Asyraf Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
description	The emergence of 3-Satisfiability (3-SAT) problem has produced a prolific number of works devoted to the field of logic and data mining. In this study, a new hybrid method in doing logic programming by incorporating 3-SAT logical rules as a computational tool will be presented. Hence, a robust intelligence system that integrates the Hopfield neural network and metaheuristic paradigm is constructed to extract the data set hidden knowledge in the form of 3-Satisfiability logical rule. A hybrid network called HNN-3SATAIS is proposed by assimilating the Hopfield neural network with the enhanced artificial immune system (AIS) algorithm as a training tool in doing 3-Satisfiability logic programming.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mansor, Mohd. Asyraf
author_facet	Mansor, Mohd. Asyraf
author_sort	Mansor, Mohd. Asyraf
title	Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
title_short	Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
title_full	Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
title_fullStr	Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
title_full_unstemmed	Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
title_sort	enhanced hopfield neural networks with artificial immune system algorithm for satisfiability logic programming
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Matematik
publishDate	2017
url	http://eprints.usm.my/45423/1/MOHD.%20ASYRAF%20MANSOR.pdf
_version_	1747821507924459520

Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming

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