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Course Detail

Course Name Computational Intelligence
Course Code 18CA334
Program M. C. A., M. C. A. ( Offered at Mysuru Campus )
Credits Three
Year Taught 2018
Degree Postgraduate (PG)
School School of Arts and Sciences, School of Engineering
Campus Kochi, Mysuru, Amritapuri


Artificial Intelligence – a Brief Review – Pitfalls of Traditional AI – Need for Computational Intelligence – Importance of Tolerance of Imprecision and Uncertainty – Constituent Techniques – Overview of Artificial Neural Networks – Fuzzy Logic – Evolutionary Computation.

Neural Network: Biological and Artificial Neuron, Neural Networks, Supervised and Unsupervised Learning. Single Layer Perceptron – Multilayer Perceptron – Backpropagation Learning.

Neural Networks as Associative Memories – Hopfield Networks, Bidirectional Associative Memory. Topologically Organized Neural Networks – Competitive Learning, Kohonen Maps.

Fuzzy Logic: Fuzzy Sets – Properties – Membership Functions – Fuzzy Operations. Fuzzy Logic and Fuzzy Inference – Applications. Evolutionary Computation – Constituent Algorithms. Swarm Intelligence Algorithms – Overview of other Bio-inspired Algorithms – Hybrid Approaches (Neural Networks, Fuzzy Logic, Genetic Algorithms etc.).

Text Books

  1. LaureneFausett, Fundamentals of Neural Networks, 2ndedition,Pearson, 1993
  2. Ross T J, “Fuzzy Logic with Engineering Applications”, McGraw Hill, 1997.
  3. Eiben A E and Smith J E, “Introduction to Evolutionary Computing”, Second Edition, Springer, Natural Computing Series, 2007.
  4. Kumar S, “Neural Networks – A Classroom Approach”, Tata McGraw Hill, 2004.
  5. Engelbrecht, A.P, “Fundamentals of Computational Swarm Intelligence”, John Wiley & Sons, 2006.
  6. Konar. A, “Computational Intelligence: Principles, Techniques and Applications”, Springer Verlag, 2005.

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