Soft Computing PDF VSSUT – SC PDF VSSUT of Total Complete Notes
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Module – 1
Introduction to Neuro, Fuzzy and Soft Computing, Fuzzy Sets : Basic Definition and Terminology,
Set-theoretic Operations, Member Function Formulation and Parameterization,
Fuzzy Rules and Fuzzy Reasoning, Extension Principle and Fuzzy Relations,
Fuzzy If-Then Rules, Fuzzy Reasoning , Fuzzy Inference Systems, Mamdani Fuzzy Models, Sugeno Fuzzy Models, Tsukamoto Fuzzy Models,
Input Space Partitioning and Fuzzy Modeling.
Module – 2
Neural networks: Single layer networks, Perceptrons: Adaline, Mutilayer Perceptrons Supervised
LM Method, Radial Basis Function Networks, Unsupervised Learning Neural Networks,
Competitive Learning Networks, Kohonen Self-Organizing Networks,
Learning Vector Quantization, Hebbian Learning. Recurrent neural networks,
Adaptive neuro-fuzzy information;systems (ANFIS), Hybrid Learning Algorithm, Applications to control and pattern recognition.
Module – 3
Derivative-free Optimization Genetic algorithms: Basic concepts, encoding, fitness function,
Basic flow chart of EA,Special features of GA,PARENT SELECTION,CROSSOVER,
ADVANTAGES AND DISADVANTAGES OF EA,Differences and similarities between GA and other traditional methods,
reproduction. Differences of GA and traditional optimization methods. Basic genetic programming
Module – 4
Evolutionary Computing, Simulated Annealing, Random Search, Downhill Simplex Search, Swarm
Drawback of traditional techniques,Analogy-based algorithms,Random search algorithms.
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. Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”,
Addison Wesley, N.Y., 1989.
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Professional, Boston, 1996.
. Stamatios V. Kartalopoulos “Understanding Neural Networks and Fuzzy Logic Basic
concepts & Applications”, IEEE Press, PHI, New Delhi, 2004.
. Vojislav Kecman, “Learning & Soft Computing Support Vector Machines, Neural Networks,
and Fuzzy Logic Models”, Pearson Education, New Delhi,2006.
 S. Rajasekaran & GA Vijayalakshmi Pai “Neural Networks, Fuzzy Logic, and Genetic
Algorithms synthesis and application”, PHI.