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Indian Institute of Technology, Kharagpur
Lecture 1 Introduction to soft computing.Lecture 2 : Introduction to Fuzzy Logic.Lecture 3 : Fuzzy membership functions (Contd.) and Defining Membership functions.Lecture 4 : Fuzzy operations.Lecture 5 : Fuzzy relations.Lecture 6 : Fuzzy Relations (contd.) & Fuzzy propositions.Lecture 7 : Fuzzy implications.Lecture 8 : Fuzzy Inferences.Lecture 9 : Defuzzification techniques (Part-I).Lecture 10 : Defuzzification Techniques (Part-I) (contd.).Lecture 11 : Fuzzy logic controller.Lecture 12 : Fuzzy Logic Controller (Contd.).Lecture 13 : Fuzzy logic controller (Cond.).Lecture 14 : Concept of Genetic Algorithm.Lecture 15 : Concept of Genetic Algorithm (Contd.) and GA Strategies.Lecture 16 : GA Operator : Encoding schemes.Lecture 17 : GA operator : encoding scheme (contd.).Lecture 18 : GA Operator : Selection.Lecture 19 : GA Operator Selection (Contd.).Lecture 20 : GA Operator: Crossover techniques.Lecture 21 : GA Operator : Crossover (Contd.).Lecture 22 : GA Operator : Crossover (Contd.).Lecture 23 : GA Operator : Mutation and others.Lecture 24 : Multi-objective optimization problem solving.Lecture 25 : Multi-objective optimization problem solving (Contd.).Lecture 26 : Concept of domination.Lecture 27 : Non-Pareto based approaches to solve MOOPs.Lecture 28 : Non-Pareto based approaches to solve MOOPs (Contd.).Lecture 29 : Pareto-Based approaches to solve MOOPs.Lecture 30 : Pareto-based approaches to solve MOOPs (contd..).Lecture 31 : Pareto-based approach to solve MOOPs.Lecture 32 : Pareto-based approach to solve MOOPs (contd.).Lecture 33 : Pareto-based approach to solve MOOPs (contd).Lecture 34 : Introduction to Artificial Neural Network.Lecture 35 : ANN Architectures.Lecture 36 : Training ANNs.Lecture 37 : Training ANNs (Contd..).Lecture 38 : Training ANNs (Contd..).Lecture 39 : Training ANNs (Contd..).Lecture 40 : Soft computing tools.
Introduction To Soft Computing - IITKGP
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