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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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Elsevier
2024
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| 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 |
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