Applications of Fuzzy Sets in Decision Analysis(IND 514)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| IND 514 | Applications of Fuzzy Sets in Decision Analysis | 2 | 3 | 0 | 0 | 3 | 6 |
| Prerequisites | |
| Admission Requirements |
| Language of Instruction | English |
| Course Type | Elective |
| Course Level | Masters Degree |
| Course Instructor(s) | Esra ALBAYRAK ealbayrak@gsu.edu.tr (Email) |
| Assistant | |
| Objective | Fuzzy sets provide a mathematical framework for the handling of uncertain and vague information and concepts. Fuzzy sets and fuzzy control theory have found many practical applications in a range of fields, such as image processing, expert systems, data mining, signal processing, and bioinformatics. This course provides the foundations of fuzzy set theory and fuzzy reasoning, as well as practical hands on experience of fuzzy techniques in various applications through computer exercises and project work. The main objective is to discuss the fundamental concepts of fuzzy logic, such as fuzzy set theory, fuzzy algebra, approximate reasoning, fuzzy measures and possibility theory. Further objectives are to mediate practical experience in the analysis, design and implementation of these concepts in form of a fuzzy system, by means of sample computational exercises. |
| Content | Fuzzy Set Theory, Fuzzy sets and classic fuzzy operators, Fuzzy Algebra, Fuzzy if-then rules and fuzzy reasoning, Extension principle, Fuzzy relations, Fuzzy inference systems, Fuzzy Logic, Fuzzy Control.,Fuzzy Expert Systems, Possibility Theory. |
| Course Learning Outcomes |
The students who succeeded in this course will be able to 1.explain fundamental concepts of fuzzy logic and fuzzy sets 2.design a fuzzy system 3.develop a fuzzy system 4.apply fuzzy logic techniques to various systems |
| Teaching and Learning Methods | |
| References |
Fuzzy Logic with Engineering Applications, Timothy J. Ross, McGraw-Hill Introduction to fuzzy systems, Guanrong Chen & Trung Tat Pham, Chapman & Hall/CRC |
Theory Topics
| Week | Weekly Contents |
|---|---|
| 1 | What is a fuzzy set? The basics of fuzzy sets, Crisp Set Theory, Basic Concepts and terminology |
| 2 | Classic fuzzy operators, Computing with Words, Fuzzy vs. probability, Extended fuzzy union, intersection, and complement |
| 3 | Fuzzy numbers and fuzzy arithmetics |
| 4 | QUIZ 1, Information and uncertainty, Properties of Membership Functions |
| 5 | Extension Principle |
| 6 | Fuzzy implications, Binary fuzzy relations |
| 7 | MIDTERM |
| 8 | Classical Relations and Fuzzy Relations, Value Assignments, Cosine Amplitude,Max–Min Method, Other Similarity Methods |
| 9 | Defuzzification Part 1 |
| 10 | Defuzzification Part 2, Alpha-Cuts for Fuzzy Relations |
| 11 | Fuzzy numbers and Interval Analysis |
| 12 | Fuzzy logic and approximate reasoning, Fuzzy if-then rules, Fuzzy reasoning |
| 13 | Fuzzy Control |
| 14 | Fuzzy inference systems, Mamdani's fuzzy models, Sugeno's fuzzy models |
Practice Topics
| Week | Weekly Contents |
|---|
Contribution to Overall Grade
| Number | Contribution | |
|---|---|---|
| Contribution of in-term studies to overall grade | 3 | 60 |
| Contribution of final exam to overall grade | 1 | 40 |
| Toplam | 4 | 100 |
In-Term Studies
| Number | Contribution | |
|---|---|---|
| Assignments | 0 | 0 |
| Presentation | 0 | 0 |
| Midterm Examinations (including preparation) | 1 | 20 |
| Project | 0 | 0 |
| Laboratory | 0 | 0 |
| Other Applications | 0 | 0 |
| Quiz | 2 | 30 |
| Term Paper/ Project | 3 | 10 |
| Portfolio Study | 0 | 0 |
| Reports | 0 | 0 |
| Learning Diary | 0 | 0 |
| Thesis/ Project | 0 | 0 |
| Seminar | 0 | 0 |
| Other | 0 | 0 |
| Toplam | 6 | 60 |
| No | Program Learning Outcomes | Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | X | |||||
| 2 | X | |||||
| 3 | X | |||||
| 4 | X | |||||
| 5 | X | |||||
| 6 | X | |||||
| 7 | X | |||||
| 8 | X | |||||
| 9 | X | |||||
| 10 | X | |||||
| 11 | ||||||
| 12 | ||||||
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 14 | 3 | 42 |
| Working Hours out of Class | 10 | 3 | 30 |
| Midterm Examinations (including preparation) | 1 | 20 | 20 |
| Final Examinations (including preparation) | 1 | 30 | 30 |
| Quiz | 2 | 15 | 30 |
| Term Paper/ Project | 3 | 10 | 30 |
| Total Workload | 182 | ||
| Total Workload / 25 | 7,28 | ||
| Credits ECTS | 7 | ||