Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
The emergence of 3-Satisfiability (3-SAT) problem has produced a prolific number of works devoted to the field of logic and data mining. In this study, a new hybrid method in doing logic programming by incorporating 3-SAT logical rules as a computational tool will be presented. Hence, a robust intel...
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
2017
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| 主题: | |
| 在线阅读: | http://eprints.usm.my/45423/1/MOHD.%20ASYRAF%20MANSOR.pdf |
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| 总结: | The emergence of 3-Satisfiability (3-SAT) problem has produced a prolific number of works devoted to the field of logic and data mining. In this study, a new hybrid method in doing logic programming by incorporating 3-SAT logical rules as a computational tool will be presented. Hence, a robust intelligence system that integrates the Hopfield neural network and metaheuristic paradigm is constructed to extract the data set hidden knowledge in the form of 3-Satisfiability logical rule. A hybrid network called HNN-3SATAIS is proposed by assimilating the Hopfield neural network with the enhanced artificial immune system (AIS) algorithm as a training tool in doing 3-Satisfiability logic programming. |
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