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

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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...

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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/ http://psasir.upm.edu.my/id/eprint/114433/1/114433.pdf

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