Dr. Saratha Sathasivam
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Dr. Saratha Sathasivam

Associate Professor
University of Science, Malaysia

Highest Degree
Ph.D. in Physics from University of Malaya, Malaysia

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Biography

Assoc.Prof.Dr.Saratha Sathasivam is a lecturer in the Universiti Sains Malaysia, School of Mathematical Sciences since 2007. She received her B.Sc (2001) in education and MSc (2003)in Mathematics from the same university. PhD degree (2007) in Physics was granted by University of Malaya, Malaysia. Her research work focused on neural networks and data mining. She has few publications related to neural networks and logic.

Area of Interest:

Physics
100%
Neural Networks
62%
Logic Programming
90%
Numerical Methods
75%
Data Mining
55%

Research Publications in Numbers

Books
0
Chapters
0
Articles
0
Abstracts
0

Selected Publications

  1. Shareduwan, M., K. Mohd, A.M. Mohd and S. Saratha, 2016. Hybrid genetic algorithm in the hopfield network for logic satisfiability problem. Pertanika J., .
  2. Shareduwan, M., K. Mohd and S. Saratha, 2016. Accelerating activation function for 3-satisfiability logic programming. Int. J. Intell. Syst., .
  3. Sagir, A.M and S. Saratha, 2016. The self organizing map as a tool for cluster analysis. Pertanika, .
  4. Mansor, M.A., S. Mohd, K. Mohd and S. Saratha, 2016. Enhanced hopfield network for pattenn satisfiabiality problem. Int. J. Intell. Syst., .
  5. Velavan, M., R.Y. Zainor, N.A.H. Mohamad and S. Saratha, 2015. Boltzmann machine and and hyperbolic activation function in higher order neuro symbolic integration. Int. J. Comput. Electr. Aspects Eng., 1: 10-14.
  6. Sathasivam, S., 2015. Acceleration technique for neuro symbolic integration. Appl. Math. Sci., 9: 409-417.
    CrossRef  |  Direct Link  |  
  7. Pwasong, A.D and S. Saratha, 2015. Forecasting performance of random walk with drift and feed forward neural network models. Int.J. Intell. Syst. Appl., 9: 49-56.
    CrossRef  |  Direct Link  |  
  8. Pwasong, A and S. Saratha, 2015. A new hybrid quadratic regression and cascade forward backpropagation neural network. Neuro Comput., 182: 197-209.
    CrossRef  |  Direct Link  |  
  9. Davou, P.A and S. Saratha, 2015. Statistical neural networks in the classification of alcoholic liver disease and nonalcoholic fatty liver disease. Int. J. Comput. Electr. Aspects Eng., 1: 5-9.
  10. Sathasivam, S and M.S. Abdu, 2014. Comparative study of euclidean and city block distances in fuzzy c-means clustering algorithm. Int. J. Comput. Electr. Aspects Eng., 1: 10-12.
    Direct Link  |  
  11. Mamuda, M and S. Saratha, 2014. Comapring logic programming in radial basis function neural network (rbfnn) and hopfield neural network. Int. J. Comput. Electr. Aspects Eng., 1: 13-19.
    Direct Link  |  
  12. Sathasivam, S., P.F. Ng and V. Muraly, 2013. Reverse analysis in higher order hopfield network for higher order horn clauses. Appl. Math. Sci., 8: 601-612.
    CrossRef  |  Direct Link  |  
  13. Sathasivam, S., P.F. Ng and H. Nawaf, 2013. Developing agent based modeling for reverse analysis method. Res. J. Appl. Sci. Eng. Technol., 6: 4281-4288.
    Direct Link  |  
  14. Sathasivam, S and P.F. Ng, 2013. Developing agent based modeling for doing logic programming in hopfield network. Appl. Math. Sci., 7: 23-35.
    Direct Link  |  
  15. Sathasivam, S and P.F. Ng, 2013. Assimilating boltzmann machine and reverse analysis method. Math. Sci. Int. Res. J., 2: 312-319.
  16. Hamadneh, N., L.T. Surafel, S. Saratha and H.C. Ong, 2013. Prey-Predator algorithm as a new optimization technique using in radial basis function neural networks. Res. J. Appl. Sci., 8: 383-387.
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  17. Sathasivam, S., 2012. Performance comparison between pseudo inverse rule and sign constraint method. Far East J. Math. Sci., 62: 51-59.
  18. Sathasivam, S., 2012. First order logic in neuro-symbolic integration. Far East J. Math. Sci., 61: 213-229.
  19. Sathasivam, S., 2012. Applying knowledge reasoning techniques in neural networks. Aust. J. Basic Appl. Sci., 6: 53-56.
    Direct Link  |  
  20. Sathasivam, S., 2012. Applying fuzzy logic in neuro symbolic integration. World Appl. Sci. J., 17: 79-86.
    Direct Link  |  
  21. Hamadneh, N., S. Sathasivam, U.L. Tilahun and O.H. Choon, 2012. Learning logic programming in radial basis function network via genetic algorithm. J. App. Sci., 12: 840-847.
    CrossRef  |  
  22. Hamadneh, N., S. Sathasivam and O.H.Choon, 2012. Higher order logic programming in radial basis function neural network. Applied Math. Sci., 6: 115-127.
    Direct Link  |  
  23. Sathasivam, S., H. Nawaf and H.C. Ong, 2011. Comparing neural networks : Hopfield network and rbf network. Appl. Math. Sci., 5: 3439-3452.
    Direct Link  |  
  24. Sathasivam, S., 2011. Boltzmann machine and new activation function comparison. Appl. Math. Sci., 5: 3853-3860.
    Direct Link  |  
  25. Sathasivam, S., 2010. Normal form representation in doing logic programming in hopfield network. Far East J. Math. Sci., 47: 185-200.
  26. Sathasivam, S., 2010. Accelerating neuro-symbolic integration by using boltzmann machine. Far East J. Math. Sci., 43: 241-251.
  27. Sathasivam, S., 2009. Logical content in the recurrent hopfield network without higher order connections. Eur. J. Sci. Res., 37: 361-367.
  28. Sathasivam, S., 2009. Enhancing logic programming performance in recurrent hopfield Eur. J. Sci. Res., 37: 6-11.