Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

This study introduced a novel ant colony optimization algorithm that implements the population selection strategy of the Estimation of Distribution Algorithm and a new pheromone updating formula. It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedde...

Full description

Saved in:
Bibliographic Details
Main Authors: Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin
Format: Article
Language:English
Published: Elsevier 2024
Online Access:http://psasir.upm.edu.my/id/eprint/114433/1/114433.pdf
http://psasir.upm.edu.my/id/eprint/114433/
https://linkinghub.elsevier.com/retrieve/pii/S1568494624009669
Tags: Add Tag
No Tags, Be the first to tag this record!