| Module Name | Download |
|---|---|
| noc20_cs17_assigment_1 | noc20_cs17_assigment_1 |
| noc20_cs17_assigment_2 | noc20_cs17_assigment_2 |
| noc20_cs17_assigment_3 | noc20_cs17_assigment_3 |
| noc20_cs17_assigment_4 | noc20_cs17_assigment_4 |
| noc20_cs17_assigment_5 | noc20_cs17_assigment_5 |
| noc20_cs17_assigment_6 | noc20_cs17_assigment_6 |
| noc20_cs17_assigment_7 | noc20_cs17_assigment_7 |
| noc20_cs17_assigment_8 | noc20_cs17_assigment_8 |
| noc20_cs17_assigment_9 | noc20_cs17_assigment_9 |
| Sl.No | Chapter Name | MP4 Download |
|---|---|---|
| 1 | Lecture 1 Introduction to soft computing | Download |
| 2 | Lecture 2 : Introduction to Fuzzy Logic | Download |
| 3 | Lecture 3 : Fuzzy membership functions (Contd.) and Defining Membership functions | Download |
| 4 | Lecture 4 : Fuzzy operations | Download |
| 5 | Lecture 5 : Fuzzy relations | Download |
| 6 | Lecture 6 : Fuzzy Relations (contd.) & Fuzzy propositions | Download |
| 7 | Lecture 7 : Fuzzy implications | Download |
| 8 | Lecture 8 : Fuzzy Inferences | Download |
| 9 | Lecture 9 : Defuzzification techniques (Part-I) | Download |
| 10 | Lecture 10 : Defuzzification Techniques (Part-I) (contd.) | Download |
| 11 | Lecture 11 : Fuzzy logic controller | Download |
| 12 | Lecture 12 : Fuzzy Logic Controller (Contd.) | Download |
| 13 | Lecture 13 : Fuzzy logic controller (Cond.) | Download |
| 14 | Lecture 14 : Concept of Genetic Algorithm | Download |
| 15 | Lecture 15 : Concept of Genetic Algorithm (Contd.) and GA Strategies | Download |
| 16 | Lecture 16 : GA Operator : Encoding schemes | Download |
| 17 | Lecture 17 : GA operator : encoding scheme (contd.) | Download |
| 18 | Lecture 18 : GA Operator : Selection | Download |
| 19 | Lecture 19 : GA Operator Selection (Contd.) | Download |
| 20 | Lecture 20 : GA Operator: Crossover techniques | Download |
| 21 | Lecture 21 : GA Operator : Crossover (Contd.) | Download |
| 22 | Lecture 22 : GA Operator : Crossover (Contd.) | Download |
| 23 | Lecture 23 : GA Operator : Mutation and others | Download |
| 24 | Lecture 24 : Multi-objective optimization problem solving | Download |
| 25 | Lecture 25 : Multi-objective optimization problem solving (Contd.) | Download |
| 26 | Lecture 26 : Concept of domination | Download |
| 27 | Lecture 27 : Non-Pareto based approaches to solve MOOPs | Download |
| 28 | Lecture 28 : Non-Pareto based approaches to solve MOOPs (Contd.) | Download |
| 29 | Lecture 29 : Pareto-Based approaches to solve MOOPs | Download |
| 30 | Lecture 30 : Pareto-based approaches to solve MOOPs (contd..) | Download |
| 31 | Lecture 31 : Pareto-based approach to solve MOOPs | Download |
| 32 | Lecture 32 : Pareto-based approach to solve MOOPs (contd.) | Download |
| 33 | Lecture 33 : Pareto-based approach to solve MOOPs (contd) | Download |
| 34 | Lecture 34 : Introduction to Artificial Neural Network | Download |
| 35 | Lecture 35 : ANN Architectures | Download |
| 36 | Lecture 36 : Training ANNs | Download |
| 37 | Lecture 37 : Training ANNs (Contd..) | Download |
| 38 | Lecture 38 : Training ANNs (Contd..) | Download |
| 39 | Lecture 39 : Training ANNs (Contd..) | Download |
| 40 | Lecture 40 : Soft computing tools | Download |
| Sl.No | Chapter Name | English |
|---|---|---|
| 1 | Lecture 1 Introduction to soft computing | Download Verified |
| 2 | Lecture 2 : Introduction to Fuzzy Logic | Download Verified |
| 3 | Lecture 3 : Fuzzy membership functions (Contd.) and Defining Membership functions | Download Verified |
| 4 | Lecture 4 : Fuzzy operations | Download Verified |
| 5 | Lecture 5 : Fuzzy relations | Download Verified |
| 6 | Lecture 6 : Fuzzy Relations (contd.) & Fuzzy propositions | Download Verified |
| 7 | Lecture 7 : Fuzzy implications | Download Verified |
| 8 | Lecture 8 : Fuzzy Inferences | Download Verified |
| 9 | Lecture 9 : Defuzzification techniques (Part-I) | Download Verified |
| 10 | Lecture 10 : Defuzzification Techniques (Part-I) (contd.) | Download Verified |
| 11 | Lecture 11 : Fuzzy logic controller | Download Verified |
| 12 | Lecture 12 : Fuzzy Logic Controller (Contd.) | Download Verified |
| 13 | Lecture 13 : Fuzzy logic controller (Cond.) | Download Verified |
| 14 | Lecture 14 : Concept of Genetic Algorithm | Download Verified |
| 15 | Lecture 15 : Concept of Genetic Algorithm (Contd.) and GA Strategies | Download Verified |
| 16 | Lecture 16 : GA Operator : Encoding schemes | Download Verified |
| 17 | Lecture 17 : GA operator : encoding scheme (contd.) | Download Verified |
| 18 | Lecture 18 : GA Operator : Selection | Download Verified |
| 19 | Lecture 19 : GA Operator Selection (Contd.) | Download Verified |
| 20 | Lecture 20 : GA Operator: Crossover techniques | Download Verified |
| 21 | Lecture 21 : GA Operator : Crossover (Contd.) | Download Verified |
| 22 | Lecture 22 : GA Operator : Crossover (Contd.) | Download Verified |
| 23 | Lecture 23 : GA Operator : Mutation and others | Download Verified |
| 24 | Lecture 24 : Multi-objective optimization problem solving | Download Verified |
| 25 | Lecture 25 : Multi-objective optimization problem solving (Contd.) | Download Verified |
| 26 | Lecture 26 : Concept of domination | Download Verified |
| 27 | Lecture 27 : Non-Pareto based approaches to solve MOOPs | Download Verified |
| 28 | Lecture 28 : Non-Pareto based approaches to solve MOOPs (Contd.) | Download Verified |
| 29 | Lecture 29 : Pareto-Based approaches to solve MOOPs | Download Verified |
| 30 | Lecture 30 : Pareto-based approaches to solve MOOPs (contd..) | Download Verified |
| 31 | Lecture 31 : Pareto-based approach to solve MOOPs | Download Verified |
| 32 | Lecture 32 : Pareto-based approach to solve MOOPs (contd.) | Download Verified |
| 33 | Lecture 33 : Pareto-based approach to solve MOOPs (contd) | Download Verified |
| 34 | Lecture 34 : Introduction to Artificial Neural Network | Download Verified |
| 35 | Lecture 35 : ANN Architectures | Download Verified |
| 36 | Lecture 36 : Training ANNs | Download Verified |
| 37 | Lecture 37 : Training ANNs (Contd..) | Download Verified |
| 38 | Lecture 38 : Training ANNs (Contd..) | Download Verified |
| 39 | Lecture 39 : Training ANNs (Contd..) | Download Verified |
| 40 | Lecture 40 : Soft computing tools | Download Verified |
| Sl.No | Chapter Name | Hindi |
|---|---|---|
| 1 | Lecture 1 Introduction to soft computing | Download |
| 2 | Lecture 2 : Introduction to Fuzzy Logic | Download |
| 3 | Lecture 3 : Fuzzy membership functions (Contd.) and Defining Membership functions | Download |
| 4 | Lecture 4 : Fuzzy operations | Download |
| 5 | Lecture 5 : Fuzzy relations | Download |
| 6 | Lecture 6 : Fuzzy Relations (contd.) & Fuzzy propositions | Download |
| 7 | Lecture 7 : Fuzzy implications | Download |
| 8 | Lecture 8 : Fuzzy Inferences | Download |
| 9 | Lecture 9 : Defuzzification techniques (Part-I) | Download |
| 10 | Lecture 10 : Defuzzification Techniques (Part-I) (contd.) | Download |
| 11 | Lecture 11 : Fuzzy logic controller | Download |
| 12 | Lecture 12 : Fuzzy Logic Controller (Contd.) | Download |
| 13 | Lecture 13 : Fuzzy logic controller (Cond.) | Download |
| 14 | Lecture 14 : Concept of Genetic Algorithm | Download |
| 15 | Lecture 15 : Concept of Genetic Algorithm (Contd.) and GA Strategies | Download |
| 16 | Lecture 16 : GA Operator : Encoding schemes | Download |
| 17 | Lecture 17 : GA operator : encoding scheme (contd.) | Download |
| 18 | Lecture 18 : GA Operator : Selection | Download |
| 19 | Lecture 19 : GA Operator Selection (Contd.) | Download |
| 20 | Lecture 20 : GA Operator: Crossover techniques | Download |
| 21 | Lecture 21 : GA Operator : Crossover (Contd.) | Download |
| 22 | Lecture 22 : GA Operator : Crossover (Contd.) | Download |
| 23 | Lecture 23 : GA Operator : Mutation and others | Download |
| 24 | Lecture 24 : Multi-objective optimization problem solving | Download |
| 25 | Lecture 25 : Multi-objective optimization problem solving (Contd.) | Download |
| 26 | Lecture 26 : Concept of domination | Download |
| 27 | Lecture 27 : Non-Pareto based approaches to solve MOOPs | Download |
| 28 | Lecture 28 : Non-Pareto based approaches to solve MOOPs (Contd.) | Download |
| 29 | Lecture 29 : Pareto-Based approaches to solve MOOPs | Download |
| 30 | Lecture 30 : Pareto-based approaches to solve MOOPs (contd..) | Download |
| 31 | Lecture 31 : Pareto-based approach to solve MOOPs | Download |
| 32 | Lecture 32 : Pareto-based approach to solve MOOPs (contd.) | Download |
| 33 | Lecture 33 : Pareto-based approach to solve MOOPs (contd) | Download |
| 34 | Lecture 34 : Introduction to Artificial Neural Network | Download |
| 35 | Lecture 35 : ANN Architectures | Download |
| 36 | Lecture 36 : Training ANNs | Download |
| 37 | Lecture 37 : Training ANNs (Contd..) | Download |
| 38 | Lecture 38 : Training ANNs (Contd..) | Download |
| 39 | Lecture 39 : Training ANNs (Contd..) | Download |
| 40 | Lecture 40 : Soft computing tools | Download |