RGTU/RGPV MCA-504 Elective EII(c) : Soft Computing Syllabus MCA 5th -Fifth sem Soft Computing Syllabus

RGTU/RGPV MCA-504 Elective EII(c) : Soft Computing Syllabus
MCA 5th Sem Soft Computing Syllabus
MCA 5th - Fourth Semester Syllabus

MCA-504 Elective EII(c) : Soft Computing Course Contents:

Introduction, Soft Computing concept explanation, brief description of separate theories. Neural Networks and Probabilistic Reasoning; Biological and artificial neuron, neural networks and their classification. Adaline, Perceptron, Madaline and BP (Back Propagation) neural networks. Adaptive feed forward multilayer networks. Algorithms: Marchand, Upstart, Cascade correlation, Tilling. RBF and RCE neural networks. Topologic organized neural network, competitive learning, Kohonen maps.

CPN , LVQ, ART, SDM and Neocognitron neural networks. Neural networks as associative memories
(Hopfield, BAM). Solving optimization problems using neural networks. Stochastic neural networks, Boltzmann machine.

Fundamentals of fuzzy sets and fuzzy logic theory, fuzzy inference principle. Examples of use of fuzzy logic in control of real-world systems.

Fundamentals of genetic programming, examples of its using in practice. Genetic Algorithms Applications of GA's – Class.

Fundamentals of rough sets and chaos theory. Hybrid approaches (neural networks, fuzzy logic, genetic algorithms, rough sets).

1. Cordón, O., Herrera, F., Hoffman, F., Magdalena, L.: Genetic Fuzzy systems, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 981-02-4016-3
2. Kecman, V.: Learning and Soft Computing, The MIT Press, 2001, ISBN 0-262-11255-8
3. Mehrotra, K., Mohan, C., K., Ranka, S.: Elements of Artificial Neural Networks, The MIT Press, 1997, ISBN 0-262-13328-8
4. Munakata, T.: Fundamentals of the New Artificial Intelligence, Springer-Verlag New York, Inc., 1998. ISBN 0-387-98302-3
5. Goldberg : Introduction to Genetic Algorithms
6. Jang, “ Nero-Fuzzy & Soft Computing”, Pearsons
Note : Paper is to be set unit wise with internal choice.

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