布尔可满足性问题的改进神经网络

2015 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE) Pub Date : 2015-11-24 DOI:10.1109/ICMEAE.2015.46

M. Mejía-Lavalle, J. Ruiz, Joaquín O. Pérez, Marilu S. Cervantes

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引用次数: 1

摘要

针对布尔可满足性np困难问题，提出了一种改进的Hopfield人工神经网络。将所提出的神经网络与该领域使用的其他传统方法(如贪心SAT和遗传算法)进行了比较。结果表明，考虑到其输出质量和响应时间速度，所提出的网络是一个很好的选择。

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Modified Neural Net for the Boolean Satisfiability Problem

A modified Hopfield Artificial Neural Network is proposed to solve effectively and efficiently Boolean Satisfiability (SAT) NP-hard problems. The proposed Neural Network is compared against other traditional methods employed in this field, such as Greedy SAT and Genetic Algorithms for SAT. The results show that the proposed network represents a good alternative given their output quality and response time speed.

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来源期刊

2015 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

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