Publication:
Optimizing Discrete Hopfield Neural Networks Using Major Random 1,3-Satisfiability And Hybrid Artificial Bee Colony

Thumbnail Image
Date
2025-09
Authors
Manoharam, Gaeithry
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Abstract
Satisfiability is a key symbolic language in Discrete Hopfield Neural Networks that contributes to the development of advanced Artificial Intelligence models. However, the absence of combined higher-orders satisfiability limits the full potential within the network. Therefore, this thesis introduces a optimizing discrete Hopfield neural networks using major random 1,3-satisfiability and hybrid artificial bee colony to evaluate the neuron behaviours within the network. The proposed logic demonstrates optimal performance compared to existing logical rules.
Description
Keywords
Optimizing Discrete Hopfield Neural Networks , Major Random 1 , 3-Satisfiability And Hybrid Artificial Bee Colony
Citation
URI
https://erepo.usm.my/handle/123456789/24503
Collections
Pusat Pengajian Sains Matematik - Tesis