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MCA 5 SEM. Subject: Soft Computing Techniques
UNIT - 1 Introduction What is soft computing?, different soft computing techniques and its comparison. Strength and weakness of various soft computing techniques.
UNIT - 2 Artificial Neural Network Biological neural network Vs Artificial neural network, Evolution of Neural Network, Neural Model and Network Architectures, ANN terminologies, Perceptron learning, Supervised learning network, Error back propogation network, Radial basis function network. Unsupervised learning network, Kohonen self organizing feature maps (SOM), Counter propagation network. Associative memory network, Bidirectional associative memory, Hopefield network. Special Neural Network Probabilistic neural Network, Simulated Annelling, Boltzman machine, Cauchy Machine.
UNIT - 3 Fuzzy Logic Crisp set Vs Fuzzy set, Operations on Fuzzy sets, Fuzzy relation, Membership function, Fuzzy arithmetic and Fuzzy measures, Fuzzy rule base and approximate reasoning, Fuzzy Inference System(FIS).
UNIT - 4 Genetic Algorithm Introduction, Biological Background Genetic Operators and Parameters, Genetic Algorithms in Problem Solving, Theoretical Foundations of Genetic Algorithms, Classification of Genetic algorithms.
UNIT - 5 Application of soft computing Application of Neural Network, Fuzzy logic and Genetic Algorithm in science and engineering, Study of popular Hybrid softcomputing techniques.
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