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International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.8, No.11, Nov. 2016

Enhanced Hopfield Network for Pattern Satisfiability Optimization

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Author(s)

Mohd. Asyraf Mansor, Mohd Shareduwan M. Kasihmuddin, Saratha Sathasivam

Index Terms

Pattern-SAT;Hopfield Network;3-Satisfiability;Hyperbolic Tangent Activation Function;McCulloch-Pitts Function

Abstract

Highly-interconnected Hopfield network with Content Addressable Memory (CAM) are shown to be extremely effective in constraint optimization problem. The emergent of the Hopfield network has producing a prolific amount of research. Recently, 3 Satisfiability (3-SAT) has becoming a tool to represent a variety combinatorial problems. Incorporated with 3-SAT, Hopfield neural network (HNN-3SAT) can be used to optimize pattern satisfiability (Pattern-SAT) problem. Hence, we proposed the HNN-3SAT with Hyperbolic Tangent activation function and the conventional McCulloch-Pitts function. The aim of this study is to investigate the accuracy of the pattern generated by our proposed algorithms. Microsoft Visual C++ 2013 is used as a platform for training, testing and validating our Pattern-SAT design. The detailed performance of HNN-3SAT of our proposed algorithms in doing Pattern-SAT will be discussed based on global pattern-SAT and running time. The result obtained from the simulation demonstrate the effectiveness of HNN-3SAT in doing Pattern-SAT.

Cite This Paper

Mohd. Asyraf Mansor, Mohd Shareduwan M. Kasihmuddin, Saratha Sathasivam,"Enhanced Hopfield Network for Pattern Satisfiability Optimization", International Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.11, pp.27-33, 2016. DOI: 10.5815/ijisa.2016.11.04

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