Artificial intelligence and knowledge representation techniques. introduction to fuzzy sets. Basic operations on fuzzy sets. Variable domains. Linguistic rules. Defuzzification process. Fuzzy controller: preliminaries & basic construction. The Approach of Mamdani. The approach of Takagi and Sugeno Design parameters of fuzzy controllers - Principles of neural networks - Learning methods - Neural networks for control and modeling - Neuro fuzzy control systems - application studies on mechanical systems.
M.Sc. in Mechanical Engineering
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content serial | Description |
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1 | Introduction to artificial intelligence systems |
2 | Introduction to fuzzy logic fuzzy sets. |
3 | Fuzzy relation properties, Membership s determination |
4 | Defuzzification process. Fuzzy controller: preliminaries & basic construction. |
5 | The Approach of Mamdani. The approach of Takagi and Sugeno |
6 | Design parameters of fuzzy controllers |
7 | Case study using fuzzy logic control |
8 | Case study using fuzzy logic control |
9 | Principles of neural networks |
10 | Learning methods |
11 | Neural networks for control and modeling |
12 | Neuro -fuzzy control systems ANFIS |
13 | Case study using ANN |
14 | Case study using ANN |
15 | Case study using ANFIS |
16 | Final Examination |
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