Introduction to Soft Computing

Introduction to Soft Computing

Introduction To Soft Computing - IITKGP via YouTube Direct link

Lecture 3 : Fuzzy membership functions (Contd.) and Defining Membership functions

3 of 40

3 of 40

Lecture 3 : Fuzzy membership functions (Contd.) and Defining Membership functions

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Introduction to Soft Computing

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

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