Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | MAT-23-128 | IntuItIonIstIc Fuzzy Sets and ApplIcatIon | Elective | 1 | 2 | 6 |
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Level of Course Unit |
Second Cycle |
Objectives of the Course |
The aim of this course is to examine the basic and advanced concepts of intuitionistic fuzzy set and logic theory, which are many field applications such as science, engineering, medicine, social sciences, and to introduce the entropy, inclusion, distance and similarity measures defined in this theory. It is also to give the interdisciplinary applications of mathematical concepts in intuitionistic fuzzy set theory. |
Name of Lecturer(s) |
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Learning Outcomes |
1 | At the end of the course, the student will have knowledge about intuitionistic fuzzy set theory and basic definitions of this theory. They can express and prove basic theorems about these concepts. | 2 | At the end of this course, the student will have knowledge of metrics and norms defined on intuitionistic fuzzy sets | 3 | At the end of this course, the student will have knowledge about intuitionistic fuzzy negations, implications, aggregation operators. They can use this operators in intuitionistic fuzzy systems | 4 | At the end of this course, the student will have knowledge definition and properties of distance, similarity, entropy and inclusion measures defined in intuitionistic fuzzy sets | 5 | At the end of this course, the student will have knowledge intuitionistic fuzzy clustering algorithms and they can use this algorithms in multi criteria decision making and image processing | 6 | At the end of this course, the student will have knowledge about structure of intuitionistic fuzzy systems and they can use these systems to solve real world problems. | 7 | At the end of this course, the student will have knowledge temporal intuitionistic knows fuzzy set and interval valued intuitionistic fuzzy set concepts. |
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Mode of Delivery |
Daytime Class |
Prerequisites and co-requisities |
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Recommended Optional Programme Components |
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Course Contents |
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Weekly Detailed Course Contents |
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1 | Introduction of intuitionistic fuzzy set theory, intuitionistic fuzzy set theoretic operations | | | 2 | Elements of intuitionistic propositional calculus | | | 3 | Intuitionistic fuzzy logics | | | 4 | Intuitionistic fuzzy normed spaces | | | 5 | Intuitionistic fuzzy metric spaces | | | 6 | Intuitionistic modal and topological operators | | | 7 | Midterm exam | | | 8 | Distance measures on intuitionistic fuzzy sets | | | 9 | Entropy and inclusion measures on intuitionistic fuzzy sets | | | 10 | Similarity measures on intuitionistic fuzzy sets | | | 11 | Intuitionistic fuzzy clustering algorithms | | | 12 | Applications of intuitionistic fuzzy clustering algorithms on image processing | | | 13 | Applications of intuitionistic fuzzy logic on control theory | | | 14 | Generalizations of intuitionistic fuzzy sets | | |
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Recommended or Required Reading |
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Planned Learning Activities and Teaching Methods |
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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 | | Work Placement(s) | |
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Workload Calculation |
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Midterm Examination | 1 | 5 | 5 |
Final Examination | 1 | 5 | 5 |
Attending Lectures | 14 | 2 | 28 |
Discussion | 14 | 1 | 14 |
Self Study | 14 | 10 | 140 |
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Contribution of Learning Outcomes to Programme Outcomes |
LO1 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | LO2 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | LO3 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | LO4 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | LO5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | LO6 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | LO7 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |
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* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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Iğdır University, Iğdır / TURKEY • Tel (pbx): +90 476
226 13 14 • e-mail: info@igdir.edu.tr
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