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Description of Individual Course Units| Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | | İŞ126Y | Fuzzy Logic | Elective | 1 | 2 | 6 |
| | Level of Course Unit | | Second Cycle | | Objectives of the Course | | The aim of this course is to teach fuzzy logic and fuzzy set theory, to make calculations using fuzzy sets and to gain the knowledge of how to use these calculations effectively. | | Name of Lecturer(s) | | Doç. Dr. Hakan PABUÇCU | | Learning Outcomes | | 1 | Students will be able to understand the basic concepts of fuzzy logic. | | 2 | Students will be able to understand and interpret fuzzy systems within the scope of fuzzy set theory | | 3 | Students will be able to model and solve problems involving uncertainty using fuzzy set theory. | | 4 | Students will be able to use the fuzzy system and artificial intelligence techniques together, and analyze-synthesize software. | | 5 | Students will be able to develop hybrid system design. |
| | Mode of Delivery | | Normal Education | | Prerequisites and co-requisities | | NO | | Recommended Optional Programme Components | | no | | Course Contents | | Fuzzy Sets; Fuzzy Set Operations; Fuzzy Relations; Fuzzy Graphs and Relationships; Fuzzy Numbers; Fuzzy Functions; Probability and Uncertainty; Fuzzy Logic; Fuzzy Inference; Fuzzy Modeling and Control; Fuzzy Expert Systems; Fuzzy Systems and Artificial Neural Networks, Application Examples. | | Weekly Detailed Course Contents | |
| 1 | Introduction to fuzzy logic | | | | 2 | Fuzzy concept of the real world problem | | | | 3 | Fuzzy sets and procedures | | | | 4 | Fuzzy measures and fuzziness measurement | | | | 5 | Fuzzy relations and membership functions | | | | 6 | Fuzzy logic | | | | 7 | Mid-term exam | | | | 8 | Probability theory | | | | 9 | Probability and fuzzy set theory | | | | 10 | Fuzzy numbers | | | | 11 | Fuzzy membership functions | | | | 12 | Fuzzy inference | | | | 13 | Fuzzy inference | | | | 14 | General evaluation and overview | | |
| | Recommended or Required Reading | | 1.Baykal,N.&Beyan,T.,Bulanık Mantık,İlke Temelleri, Bıçakcılar Kitapevi,Ankara,2004.
2.Baykal,N.&Beyan,T.,Bulanık Mantık,Uzman Sistemler ve Denetleyiciler, Bıçakcılar Kitapevi,Ankara,2004.
3.Klir,J. G . & Yuan Bo,Fuzzy Sets and Fuzzy Logic,Theory and Applications,Prentice Hall, PTR, New Jersey,1995.
4. Dubois , D. & Prade, Henri,Fuzzy Sets and Systems,Theory and Applications, Academic Press,New York,1980.
5.Klir,J. G . & Folger, T.,,Fuzzy Sets,Uncertainty and Information,Prentice Hall,New Jersey,1988.
6 - A. Kauffmann ,Introduction to the Theory of Fuzzy Sets.
7- Ross, T.J., Fuzzy Logic with Engineering Applications, Mc-Graw Hill, 1995.
8- Lee, K. H., First Course on Fuzzy Theory and Applications, Springer Verlag, 2005.
9-H. T. Nguyen, E.A. Walker, A First Course in Fuzzy Logic, CRC Press, 2006. | | Planned Learning Activities and Teaching Methods | | | Assessment Methods and Criteria | |
| Midterm Examination | 1 | 100 | | SUM | 100 | |
| Final Examination | 1 | 100 | | SUM | 100 | | Term (or Year) Learning Activities | 40 | | End Of Term (or Year) Learning Activities | 60 | | SUM | 100 |
| | Language of Instruction | | Turkish | | Work Placement(s) | | no |
| | Workload Calculation | |
| Midterm Examination | 1 | 1 | 1 | | Final Examination | 1 | 2 | 2 | | Attending Lectures | 14 | 3 | 42 | | Self Study | 14 | 5 | 70 | | Individual Study for Mid term Examination | 1 | 25 | 25 | | Individual Study for Final Examination | 1 | 30 | 30 | | Homework | 5 | 2 | 10 | |
| Contribution of Learning Outcomes to Programme Outcomes | | LO1 | 2 | 3 | 1 | 2 | 2 | 3 | | LO2 | 2 | 4 | 3 | 3 | 3 | 1 | | LO3 | 3 | 4 | 2 | 2 | 2 | 2 | | LO4 | 1 | 3 | 2 | 3 | 4 | 1 | | LO5 | 2 | 1 | 3 | 2 | 4 | 3 |
| | * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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