Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability

• Main Authors: Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul
• Format: Article
• Language: English
• Published: American Institute of Mathematical Sciences 2024
• Online Access: http://psasir.upm.edu.my/id/eprint/114273/1/114273.pdf; http://psasir.upm.edu.my/id/eprint/114273/; http://www.aimspress.com/article/doi/10.3934/math.20241087

Evaluating behavioral patterns through logic mining within a given dataset has become a primary focus in current research. Unfortunately, there are several weaknesses in the research regarding the logic mining models, including an uncertainty of the attribute selected in the model, random distributi...