Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network

The representation of 2 Satisfiability problem or 2SAT is increasingly viewed as a significant logical rule in order to synthesize many real life applications. Although there were many researchers proposed the solution of 2SAT, little attention has been paid to the significance of the 2SAT logical r...

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Main Author:	Kho, Liew Ching
Format:	Thesis
Language:	English
Published:	2019
Subjects:	QA1 Mathematics (General)
Online Access:	http://eprints.usm.my/55729/1/24%20Pages%20from%20Kho%20Liew%20Ching.pdf
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spelling	my-usm-ep.557292022-11-23T04:34:16Z Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network 2019-12 Kho, Liew Ching QA1 Mathematics (General) The representation of 2 Satisfiability problem or 2SAT is increasingly viewed as a significant logical rule in order to synthesize many real life applications. Although there were many researchers proposed the solution of 2SAT, little attention has been paid to the significance of the 2SAT logical rule itself. It can be hypothesized that 2SAT property can be used as a logical rule in the intelligent system. To verify this claim, 2 Satisfiability logic programming was embedded to Hopfield neural network (HNN) as a single unit. Learning in HNN will be inspired by Wan Abdullah method since the conventional Hebbian learning is inefficient when dealing with large number of constraints. As the number of 2SAT clauses increased, the efficiency and effectiveness of the learning phase in HNN deteriorates. Swarm intelligence metaheuristic algorithm has been introduced to reduce the learning complexity of the network. The newly proposed metaheuristic algorithm was enhanced ant colony optimization (ACO) algorithm. 2019-12 Thesis http://eprints.usm.my/55729/ http://eprints.usm.my/55729/1/24%20Pages%20from%20Kho%20Liew%20Ching.pdf application/pdf en public masters Universiti Sains Malaysia Pusat Pengajian Sains Matematik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA1 Mathematics (General)
spellingShingle	QA1 Mathematics (General) Kho, Liew Ching Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
description	The representation of 2 Satisfiability problem or 2SAT is increasingly viewed as a significant logical rule in order to synthesize many real life applications. Although there were many researchers proposed the solution of 2SAT, little attention has been paid to the significance of the 2SAT logical rule itself. It can be hypothesized that 2SAT property can be used as a logical rule in the intelligent system. To verify this claim, 2 Satisfiability logic programming was embedded to Hopfield neural network (HNN) as a single unit. Learning in HNN will be inspired by Wan Abdullah method since the conventional Hebbian learning is inefficient when dealing with large number of constraints. As the number of 2SAT clauses increased, the efficiency and effectiveness of the learning phase in HNN deteriorates. Swarm intelligence metaheuristic algorithm has been introduced to reduce the learning complexity of the network. The newly proposed metaheuristic algorithm was enhanced ant colony optimization (ACO) algorithm.
format	Thesis
qualification_level	Master's degree
author	Kho, Liew Ching
author_facet	Kho, Liew Ching
author_sort	Kho, Liew Ching
title	Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
title_short	Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
title_full	Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
title_fullStr	Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
title_full_unstemmed	Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
title_sort	hybrid ant colony optimization for two satisfiability programming in hopfield neural network
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Matematik
publishDate	2019
url	http://eprints.usm.my/55729/1/24%20Pages%20from%20Kho%20Liew%20Ching.pdf
_version_	1776101109662744576

Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network

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