-To teach the students the basic concepts of fuzzy modeling, which is different than the idea of deterministic and stochastic modeling, to enrich their perspectives of the problems they will face as industrial engineers, and to help them develop different solutions.
-To exemplify the problems that can be solved by using fuzzy modeling in various industrial engineering problems.
-To demonstrate that it is possible to digitize through fuzzy modeling in events that do not have precise results and recursive characteristics.
Prerequisite(s)
None
Corequisite(s)
None
Special Requisite(s)
None
Instructor(s)
Assist. Prof. Dr. Duygun Fatih Demirel
Course Assistant(s)
Schedule
This course is not offered in this semester.
Office Hour(s)
Monday 14:00-15:45
Teaching Methods and Techniques
- During the lesson, the basic concepts are explained with the help of projection, student presentations, discussions, examinations and etc. In addition, the knowledge of students will be enhanced with homework assignments and article reviews.
Principle Sources
- H.J. Zimmermann, Fuzzy Set Theory and Its Applications, 4th edition, Kluwer Academic Publishers.
- T.J. Ross, Fuzzy Logic with Engineering Applications, 3rd edition, Wiley.
- G.J. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall.
Other Sources
-
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction to Fuzzy Sets
Oral Presentation
2. Week
Basic Definitions in Fuzzy Sets
Oral Presentation
3. Week
Membership Functions and Operations on Fuzzy Sets
Oral Presentation
4. Week
Fuzzy Numbers, Ranking, and Linguistic Variables
Oral Presentation
5. Week
Defuzzification and Extension Principle
Oral Presentation
6. Week
Fuzzy Relations
Oral Presentation
7. Week
Fuzzy Time Series
Oral Presentation
8. Week
Midterm
9. Week
Expert Systems and Fuzzy Control
Oral Presentation
10. Week
Decision Making in Fuzzy Environments
Oral Presentation
11. Week
Decision Making in Fuzzy Environments
Oral Presentation
12. Week
Fuzzy Set Models in Operations Research
Oral Presentation
13. Week
Fuzzy Set Models in Operations Research
Oral Presentation
14. Week
Article Presentations
Oral Presentation
15. Week
Article Presentations
Oral Presentation
16. Week
Final Exam
17. Week
Final Exam
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
30
Quizzes
3
5
Homework / Term Projects / Presentations
3
10
Attendance
1
5
Article Presentations
1
5
Final Exam
1
45
Program Outcomes
PO-1
Ability to apply theoretical and practical knowledge gained by Mathematics, Science and their engineering fields and ability to use their knowledge in solving complex engineering problems.
PO-2
Ability of determining, defining, formulating and solving complex engineering problems; for that purpose develop the ability of selecting and implementing suitable models and methods of analysis.
PO-3
Ability of designing a complex system, process, device or product under real world constraints and conditions serving certain needs; for this purpose ability of applying modern design techniques
PO-4
Ability of selecting and using the modern techniques and devices which are necessary for analyzing and solving complex problems in engineering implementations; ability of efficient usage of information technologies.
PO-5
Ability of designing experiments, conducting tests, collecting data and analyzing and interpreting the solutions to investigate of complex engineering problems or discipline-specific research topics.
PO-6
Ability of working efficiently in intra-disciplinary and multi-disciplinary teams; individual working ability and habits.
PO-7
Ability of verbal and written communication skills; and at least one foreign language skills, ability to write effective reports and understand written reports, ability to prepare design and production reports, ability to make impressive presentation, ability to give and receive clear and understandable instructions
PO-8
Awareness of importance of lifelong learning; ability to access data, to follow up the recent innovation in science and technology for continuous self-improvement.
PO-9
Conformity to ethical principles; knowledge about occupational and ethical responsibility, and standards used in engineering applications.
PO-10
Knowledge about work life implementations such as project management, risk management and change management; awareness about entrepreneurship and innovativeness; knowledge about sustainable development.
PO-11
Knowledge about effects of engineering applications on health, environment and security in global and social dimensions, and on the problems of the modern age in engineering; awareness about legal outcomes of engineering solutions.
Learning Outcomes
LO-1
Recall basic principles of fuzzy modelling
LO-2
Compare traditional mathematic and fuzzy mathematic, define membership function, fuzzy set operators and fuzzy decision making
LO-3
Develop fuzzy models for various engineering problems
LO-4
Define the contribution of fuzzy modelling to real life implementation
LO-5
Explain fuzzy linguistic as a philosophy of fuzzy modelling
