Application of Soft Computing (Elective-II)

Unit I

Neural Networks-I (Introduction & Architecture): Neuron, Nerve Structure and Synapse, Artificial Neuron and its Model, Activation Functions, Neural Network Architecture — Single Layer and Multilayer Feed Forward Networks, Recurrent Networks, Various Learning Techniques, Perception and Convergence Rule, Auto-associative and Hetero-associative Memory.

Unit II

Neural Networks-II (Backpropagation Networks): Perceptron Model, Single Layer ANN, Multilayer Perception Model, Backpropagation Learning Methods, Effect of Learning Rule Coefficient, Backpropagation Algorithm, Factors Affecting Backpropagation Training, Applications.

Unit III

Fuzzy Logic-I (Introduction): Basic Concepts of Fuzzy Logic, Fuzzy Sets and Crisp Sets, Fuzzy Set Theory and Operations, Properties of Fuzzy Sets, Fuzzy and Crisp Relations, Fuzzy to Crisp Conversion.

Unit IV

Fuzzy Logic-II (Membership, Rules): Membership Functions, Inference in Fuzzy Logic, Fuzzy If-Then Rules, Fuzzy Implications and Fuzzy Algorithms, Fuzzification & Defuzzification, Fuzzy Controller, Industrial Applications.

Unit V

Genetic Algorithm (GA): Basic Concepts, Working Principle, Procedures and Flow Chart of GA, Genetic Representations (Encoding), Initialization and Selection, Genetic Operators, Mutation, Generational Cycle, Applications.