Boltzmann Machine and Hyperbolic activation function in Higher Order Neuro Symbolic Integration

Muraly Velavan, Zainor Ridzuan bin Yahya, Mohamad Nazri bin Abdul Halif, Saratha Sathasivam
Volume 1: Issue 2, Revised on – 30 June 2020, pp 63-69


Author's Information
Muraly Velavan1 
Corresponding Author
1Institute of Engineering Mathematics, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
dsmuraly@yahoo.com

Zainor Ridzuan bin Yahya1
1Institute of Engineering Mathematics, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia


Mohamad Nazri bin Abdul Halif2
2School of Microelectronic Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia


Saratha Sathasivam3
2School of Mathematical Sciences, Universiti Sains Malaysia Penang, 11800 USM, Malaysia


Research Article -- Peer Reviewed
First online on – 30 March 2015,      Revised on – 30 June 2020

Open Access article under Creative Commons License

Cite this article –Muraly Velavan, Zainor Ridzuan bin Yahya, Mohamad Nazri bin Abdul Halif, Saratha Sathasivam, “Boltzmann Machine and Hyperbolic activation function in Higher Order Neuro Symbolic Integration”, International Journal of Computational and Electronics Aspects in Engineering, RAME Publishers, vol. 1, issue 2, pp. 63-69, 2015, Revised in 2020.
https://doi.org/10.26706/ijceae.1.2.20150103


Abstract:-
Higher-order network structure isimportant in doing higher order programming because high-order neural networks have converge faster and have a higher memory and story capacity. Furthermore higher order networks also have higher approximation ability and robust if compare lower-order neural networks. Thus, the higher-order clauses for logic programming in Hopfield Networks are been focused in this paper. We will limit till fifth order network due to complexity issue. Hereby we employed Boltzmann Machines and hyperbolic tangent activation function to increased the performance of neuro symbolic integration. We used agent based modelling to model this problem.
Index Terms:-
Boltzmann machine, agent based modelling and hyperbolic tangent activation function
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