Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network

In the current Artificial Neural Network research development, symbolic logical structure plays a vital role for describing the concept of intelligence. The existing Discrete Hopfield Neural Network with systematic Satisfiability logical structures failed to produce non-repetitive final neuron st...

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Main Author:	Karim, Syed Anayet
Format:	Thesis
Language:	English
Published:	2023
Subjects:	QA1-939 Mathematics
Online Access:	http://eprints.usm.my/60766/1/SYED%20ANAYET%20KARIM%20-%20TESIS24.pdf
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id	my-usm-ep.60766
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spelling	my-usm-ep.607662024-06-27T04:48:42Z Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network 2023-08 Karim, Syed Anayet QA1-939 Mathematics In the current Artificial Neural Network research development, symbolic logical structure plays a vital role for describing the concept of intelligence. The existing Discrete Hopfield Neural Network with systematic Satisfiability logical structures failed to produce non-repetitive final neuron states which tends to local minima solutions. In this regard, this thesis proposed non-systematic Random k Satisfiability logic for 3 k  , where k generates maximum three types of logical combinations (k=1,3; k=2,3; k=1,2,3) to report the behaviours of higher-order multiple logical structures. To analyse the logical combinations of Random k Satisfiability, this thesis will conduct experimentations with several performance metrics. The analysis revealed that the k=2,3 combination of Random k Satisfiability has more consistent interpretation and global solutions compared to the other combinations. Moreover, the optimal performance of Random k Satisfiability logic can be achieved by applying an efficient algorithm during the training phase of Discrete Hopfield Neural Network. One of the major features of an efficient algorithm is to make a proper balance in the exploration and exploitation strategy. In this regard, this thesis proposed a hybridized algorithm named Hybrid Election Algorithm that can well maintain the exploration-exploitation strategy. 2023-08 Thesis http://eprints.usm.my/60766/ http://eprints.usm.my/60766/1/SYED%20ANAYET%20KARIM%20-%20TESIS24.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 Karim, Syed Anayet Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network
description	In the current Artificial Neural Network research development, symbolic logical structure plays a vital role for describing the concept of intelligence. The existing Discrete Hopfield Neural Network with systematic Satisfiability logical structures failed to produce non-repetitive final neuron states which tends to local minima solutions. In this regard, this thesis proposed non-systematic Random k Satisfiability logic for 3 k  , where k generates maximum three types of logical combinations (k=1,3; k=2,3; k=1,2,3) to report the behaviours of higher-order multiple logical structures. To analyse the logical combinations of Random k Satisfiability, this thesis will conduct experimentations with several performance metrics. The analysis revealed that the k=2,3 combination of Random k Satisfiability has more consistent interpretation and global solutions compared to the other combinations. Moreover, the optimal performance of Random k Satisfiability logic can be achieved by applying an efficient algorithm during the training phase of Discrete Hopfield Neural Network. One of the major features of an efficient algorithm is to make a proper balance in the exploration and exploitation strategy. In this regard, this thesis proposed a hybridized algorithm named Hybrid Election Algorithm that can well maintain the exploration-exploitation strategy.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Karim, Syed Anayet
author_facet	Karim, Syed Anayet
author_sort	Karim, Syed Anayet
title	Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network
title_short	Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network
title_full	Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network
title_fullStr	Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network
title_full_unstemmed	Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network
title_sort	multi-objective hybrid election algorithm for random k satisfiability in discrete hopfield neural network
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Matematik
publishDate	2023
url	http://eprints.usm.my/60766/1/SYED%20ANAYET%20KARIM%20-%20TESIS24.pdf
_version_	1804888996427333632

Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network

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