Faculty of Engineering and Natural Sciences · Electrical & Electronics Engineering (English 30%) · Undergraduate
ECTS: 5 T+P+L: 3+0+0 Departmental Elective
Coordinator: Dr. Öğr. Üyesi Yakup CEZAYİRLİ
Instructors: Dr. Öğr. Üyesi Yakup CEZAYİRLİ
Course Objective
The course is designed to give a solid grounding of fundamental concepts of fuzzy logic and its applications. The course level is chosen so that all students aspiring to be a part of computational intelligence should learn these concepts shortly.
Course Content
This course presents an introductory coverage of fuzzy logic, including basic principles from an interdisciplinary perspective. It includes the concept of evolving a fuzzy set and fuzzy set operations, fuzzification rule base design and defuzzification, and simple guidelines for fuzzy sets design and selected applications.
Teaching Methods
ExpressionQuestion-AnswerDiscussionExercise and PracticeGroup StudySimulationProblem Solving
Assessment & Evaluation
HomeworkPerformance Assignment ( Lab / Workshop / Field Work / Seminar / Presentation / Completion Study / ThesisProject / DesignTesting (Essay / Tests: True-Falls, multiple-choice, short answer, matching)
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 15 | 3 | 45 |
| Out of Class Study Period | 8 | 3 | 24 |
| Midterm | 1 | 6 | 6 |
| Quiz | 5 | 2 | 10 |
| Assignment | 5 | 2 | 10 |
| Practice | 8 | 3 | 24 |
| Final | 1 | 6 | 6 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | Introduction and Fuzzy Sets Theory | Fundamental concepts of fuzzy logic, history, and its importance in engineering applications. |
| 2 | Set Theoretic Operations | Definition, properties, and engineering applications of different membership functions. |
| 3 | Membership Functions | Fuzzy set operations: intersection, union, complement, with example applications. |
| 4 | Fuzzy Relations | Fuzzy numbers, arithmetic operations on fuzzy numbers, and practical examples. |
| 5 | Fuzzy Arithmetic | Definition, classification, and example applications of fuzzy relations. |
| 6 | Fuzzy Inference Systems I | Basic principles of fuzzy inference, introduction to the Mamdani model. |
| 7 | Fuzzy Inference Systems II | Advanced inference rules and assessment of first-half course topics. |
| 8 | Midterm | |
| 9 | Fuzzifiers and Defuzzifiers I | Methods of fuzzification and defuzzification, with examples and applications. |
| 10 | Fuzzifiers and Defuzzifiers II | Design and evaluation of fuzzification/defuzzification for selected engineering problems. |
| 11 | Takagi-Sugeno Fuzzy Model | Fundamentals, mathematical formulation, and example applications of the Takagi-Sugeno model. |
| 12 | Adaptive Neuro-fuzzy Inference System (ANFIS) | Structure, learning algorithms, and practical examples of ANFIS. |
| 13 | MATLAB & Fuzzy Logic Toolbox | Design, simulation, and analysis of fuzzy systems using MATLAB. |
| 14 | MATLAB & Fuzzy Logic Toolbox | Design, simulation, and analysis of fuzzy systems using MATLAB. |
| 15 | Project Submission | Student project presentations and evaluation. |
| 16 | Final Exam |