Course Detail
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| INTRODUCTION to FUZZY LOGIC and MODELING | IND4216266 | Spring Semester | 3+0 | 3 | 6 |
| Course Program | Perşembe 08:00-08:45 Perşembe 09:00-09:45 Perşembe 10:00-10:45 |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN |
| Name of Lecturer(s) | Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN |
| Assistant(s) | Res. Asst. Ahmed Arif Şengil ([email protected]) |
| Aim | The main purpose of this course is to introduce students to the basic areas of fuzzy set theory and fuzzy logic, to provide them with the skills to express and reason many uncertainties that may arise in real-world applications of any decision-making process, and to enable students to apply these skills to engineering problems. |
| Course Content | This course contains; Introduction to Fuzzy Logic,Fuzzy Logic Concept and Uncertainty,Fuzzy Sets,Fuzzy Set Operations,Fuzzy Set Relations,Defuzzification of Fuzzy Sets,Membership Functions and Fuzzy Arithmetic,Midterm Exam,Fuzzy Inference System - Mamdani/ Sugeno/ Tsukamato Functions,Fuzzy Multi Criteria Decision-Making,Fuzzy Multi Criteria Decision-Making,Fuzzy Mathematical Modelling - Linear Programming,Fuzzy Mathematical Modelling - Goal Programming,Project Presentations,Final Exam. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 1. Students can use the knowledge they have gained to apply basic modeling and decision-making techniques in engineering. | 1, 12, 14 | A, E, F |
| 2. They know the fuzzy logic applications in different fields through analysis operations on fuzzy sets. | 13, 37 | E, F, R |
| 3. They know the fuzzy logic applications using Python programming language and MS Excel. | 11, 21, 37 | E, H |
| 4. They can evaluate real-life problems analytically. | 1, 12, 14 | A |
| 5. They can obtain more realistic results in the evaluation of events. | 2, 3, 4 | E, F |
| Teaching Methods: | 1: Mastery Learning, 11: Demonstration Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 2: Project Based Learning Model, 21: Simulation Technique, 3: Problem Baded Learning Model, 37: Computer-Internet Supported Instruction, 4: Inquiry-Based Learning |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task, H: Performance Task, R: Simulation-Based Evaluation |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Fuzzy Logic | Text Book - Chapter 1 and Lecture Notes |
| 2 | Fuzzy Logic Concept and Uncertainty | Text Book - Chapter 1 and Lecture Notes |
| 3 | Fuzzy Sets | Text Book - Chapter 2 and Lecture Notes |
| 4 | Fuzzy Set Operations | Text Book - Chapter 2 and Lecture Notes |
| 5 | Fuzzy Set Relations | Text Book - Chapter 3 and Lecture Notes |
| 6 | Defuzzification of Fuzzy Sets | Text Book - Chapter 4 and Lecture Notes |
| 7 | Membership Functions and Fuzzy Arithmetic | Text Book - Chapter 4 and Lecture Notes |
| 8 | Midterm Exam | Text Book, Lecture Notes, Assignments and Quizzes |
| 9 | Fuzzy Inference System - Mamdani/ Sugeno/ Tsukamato Functions | Text Book - Chapter 5 and Lecture Notes |
| 10 | Fuzzy Multi Criteria Decision-Making | Supplementary Book - p. 360 - 400 and Lecture Notes |
| 11 | Fuzzy Multi Criteria Decision-Making | Lecture Notes |
| 12 | Fuzzy Mathematical Modelling - Linear Programming | Supplementary Book - p. 455 - 472 and Lecture Notes |
| 13 | Fuzzy Mathematical Modelling - Goal Programming | Supplementary Book - p. 503 - 513 and Lecture Notes |
| 14 | Project Presentations | Text Book, Supplementary Book and Lecture Notes |
| 15 | Final Exam | Text Book, Lecture Notes, Assignments and Quizzes |
| Resources |
| Text Book: Fuzzy Logic with Engineering Applications, 4th Edition, Timothy J. Ross ISBN: 978-1-119-23584-2, September 2016. |
| Supplementary Book: Decision making with spherical fuzzy sets, Studies in fuzziness and soft computing, 392, pp.3-25,Kahraman, C. and Gündogdu, F.K., 2021. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
| 2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
| 3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | ||||||
| 4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
| 5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | X | |||||
| 6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | X | |||||
| 7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | X | |||||
| 8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | ||||||
| 9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | ||||||
| 10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
| 11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 30 | |
| Rate of Final Exam to Success | 70 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| Course Hours | 14 | 3 | 42 | |||
| Guided Problem Solving | 14 | 2 | 28 | |||
| Resolution of Homework Problems and Submission as a Report | 5 | 4 | 20 | |||
| Term Project | 0 | 0 | 0 | |||
| Presentation of Project / Seminar | 1 | 10 | 10 | |||
| Quiz | 8 | 8 | 64 | |||
| Midterm Exam | 1 | 8 | 8 | |||
| General Exam | 1 | 8 | 8 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 180 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(180/30) | 6 | |||||
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. | ||||||
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| INTRODUCTION to FUZZY LOGIC and MODELING | IND4216266 | Spring Semester | 3+0 | 3 | 6 |
| Course Program | Perşembe 08:00-08:45 Perşembe 09:00-09:45 Perşembe 10:00-10:45 |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN |
| Name of Lecturer(s) | Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN |
| Assistant(s) | Res. Asst. Ahmed Arif Şengil ([email protected]) |
| Aim | The main purpose of this course is to introduce students to the basic areas of fuzzy set theory and fuzzy logic, to provide them with the skills to express and reason many uncertainties that may arise in real-world applications of any decision-making process, and to enable students to apply these skills to engineering problems. |
| Course Content | This course contains; Introduction to Fuzzy Logic,Fuzzy Logic Concept and Uncertainty,Fuzzy Sets,Fuzzy Set Operations,Fuzzy Set Relations,Defuzzification of Fuzzy Sets,Membership Functions and Fuzzy Arithmetic,Midterm Exam,Fuzzy Inference System - Mamdani/ Sugeno/ Tsukamato Functions,Fuzzy Multi Criteria Decision-Making,Fuzzy Multi Criteria Decision-Making,Fuzzy Mathematical Modelling - Linear Programming,Fuzzy Mathematical Modelling - Goal Programming,Project Presentations,Final Exam. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 1. Students can use the knowledge they have gained to apply basic modeling and decision-making techniques in engineering. | 1, 12, 14 | A, E, F |
| 2. They know the fuzzy logic applications in different fields through analysis operations on fuzzy sets. | 13, 37 | E, F, R |
| 3. They know the fuzzy logic applications using Python programming language and MS Excel. | 11, 21, 37 | E, H |
| 4. They can evaluate real-life problems analytically. | 1, 12, 14 | A |
| 5. They can obtain more realistic results in the evaluation of events. | 2, 3, 4 | E, F |
| Teaching Methods: | 1: Mastery Learning, 11: Demonstration Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 2: Project Based Learning Model, 21: Simulation Technique, 3: Problem Baded Learning Model, 37: Computer-Internet Supported Instruction, 4: Inquiry-Based Learning |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task, H: Performance Task, R: Simulation-Based Evaluation |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Fuzzy Logic | Text Book - Chapter 1 and Lecture Notes |
| 2 | Fuzzy Logic Concept and Uncertainty | Text Book - Chapter 1 and Lecture Notes |
| 3 | Fuzzy Sets | Text Book - Chapter 2 and Lecture Notes |
| 4 | Fuzzy Set Operations | Text Book - Chapter 2 and Lecture Notes |
| 5 | Fuzzy Set Relations | Text Book - Chapter 3 and Lecture Notes |
| 6 | Defuzzification of Fuzzy Sets | Text Book - Chapter 4 and Lecture Notes |
| 7 | Membership Functions and Fuzzy Arithmetic | Text Book - Chapter 4 and Lecture Notes |
| 8 | Midterm Exam | Text Book, Lecture Notes, Assignments and Quizzes |
| 9 | Fuzzy Inference System - Mamdani/ Sugeno/ Tsukamato Functions | Text Book - Chapter 5 and Lecture Notes |
| 10 | Fuzzy Multi Criteria Decision-Making | Supplementary Book - p. 360 - 400 and Lecture Notes |
| 11 | Fuzzy Multi Criteria Decision-Making | Lecture Notes |
| 12 | Fuzzy Mathematical Modelling - Linear Programming | Supplementary Book - p. 455 - 472 and Lecture Notes |
| 13 | Fuzzy Mathematical Modelling - Goal Programming | Supplementary Book - p. 503 - 513 and Lecture Notes |
| 14 | Project Presentations | Text Book, Supplementary Book and Lecture Notes |
| 15 | Final Exam | Text Book, Lecture Notes, Assignments and Quizzes |
| Resources |
| Text Book: Fuzzy Logic with Engineering Applications, 4th Edition, Timothy J. Ross ISBN: 978-1-119-23584-2, September 2016. |
| Supplementary Book: Decision making with spherical fuzzy sets, Studies in fuzziness and soft computing, 392, pp.3-25,Kahraman, C. and Gündogdu, F.K., 2021. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
| 2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
| 3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | ||||||
| 4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
| 5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | X | |||||
| 6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | X | |||||
| 7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | X | |||||
| 8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | ||||||
| 9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | ||||||
| 10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
| 11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 30 | |
| Rate of Final Exam to Success | 70 | |
| Total | 100 | |