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

Mansor, Mohd. Asyraf (2017) Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming. PhD thesis, Universiti Sains Malaysia.

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Abstract

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.

Item Type: Thesis (PhD)
Subjects: Q Science > QA Mathematics > QA1-939 Mathematics
Divisions: Pusat Pengajian Sains Matematik (School of Mathematical Sciences) > Thesis
Depositing User: ASM Ab Shukor Mustapa
Date Deposited: 17 Sep 2019 01:54
Last Modified: 17 Sep 2019 01:54
URI: http://eprints.usm.my/id/eprint/45423

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