Manoharam, Gaeithry (2025) Optimizing Discrete Hopfield Neural Networks Using Major Random 1,3-Satisfiability And Hybrid Artificial Bee Colony. PhD thesis, Universiti Sains Malaysia.
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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.
| Item Type: | Thesis (PhD) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA1-939 Mathematics |
| Divisions: | Pusat Pengajian Sains Matematik (School of Mathematical Sciences) > Thesis |
| Depositing User: | Mr Aizat Asmawi Abdul Rahim |
| Date Deposited: | 26 Jun 2026 01:39 |
| Last Modified: | 26 Jun 2026 01:39 |
| URI: | http://eprints.usm.my/id/eprint/64488 |
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