Course Name |
Fuzzy Optimization
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
MATH 671
|
Fall/Spring
|
3
|
0
|
3
|
7.5
|
Prerequisites |
None
|
|||||
Course Language |
English
|
|||||
Course Type |
Elective
|
|||||
Course Level |
Third Cycle
|
|||||
Mode of Delivery | - | |||||
Teaching Methods and Techniques of the Course | - | |||||
National Occupation Classification | - | |||||
Course Coordinator | - | |||||
Course Lecturer(s) | ||||||
Assistant(s) | - |
Course Objectives | Fuzzy Set Theory is the approach to solve the problems that cannot be solved by classical set theory or probability theory. In this course, Fuzzy Set Theory and the basis of fuzyy logic will be examined. It also describes, fuzzy logic applications such as fuzzy control and fuzzy decision making, disucced in the areas of optimization. |
Learning Outcomes |
The students who succeeded in this course;
|
Course Description | The course covers basic concepts and applications of Fuzzy Set Theory. |
|
Core Courses | |
Major Area Courses | ||
Supportive Courses | ||
Media and Management Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Related Preparation | Learning Outcome |
1 | Fuzzy Sets Basic Definitions | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
2 | Fuzzy Sets Basic Definitions | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
3 | Fuzzy Measures and Fuzziness Measurements | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
4 | Fuzzy Measures and Fuzziness Measurements | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
5 | Fuzzy Relations and Fuzzy Graphics | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
6 | Fuzzy Relations and Fuzzy Graphics | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
7 | Possibility Theory, Probability Theory and Fuzzy Set Theory | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
8 | Possibility Theory, Probability Theory and Fuzzy Set Theory | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
9 | Fuzzy Logic | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
10 | Midterm | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
11 | Decision Makig in Fuzzy Environment | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
12 | Decision Makig in Fuzzy Environment | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
13 | Decision Makig in Fuzzy Environment | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
14 | Decision Makig in Fuzzy Environment | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
15 | Review | Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc. | |
16 | Review of the Semester |
Course Notes/Textbooks | Some chapters and exercises of the above books will be used. |
Suggested Readings/Materials | Fuzzy Logic with Engineering Applications by T.J. Ross, McGrawHill Book Company, 1995. |
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury |
1
|
30
|
Project | ||
Seminar / Workshop | ||
Oral Exams | ||
Midterm |
1
|
30
|
Final Exam |
1
|
40
|
Total |
Weighting of Semester Activities on the Final Grade |
60
|
|
Weighting of End-of-Semester Activities on the Final Grade |
40
|
|
Total |
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
3
|
48
|
Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
0
|
|
Study Hours Out of Class |
15
|
6
|
90
|
Field Work |
0
|
||
Quizzes / Studio Critiques |
0
|
||
Portfolio |
0
|
||
Homework / Assignments |
0
|
||
Presentation / Jury |
1
|
0
|
|
Project |
1
|
30
|
30
|
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
1
|
30
|
30
|
Final Exam |
1
|
30
|
30
|
Total |
228
|
#
|
PC Sub | Program Competencies/Outcomes |
* Contribution Level
|
||||
1
|
2
|
3
|
4
|
5
|
|||
1 | Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information. |
-
|
-
|
-
|
-
|
X
|
|
2 | Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations. |
-
|
-
|
-
|
X
|
-
|
|
3 | Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines. |
-
|
-
|
-
|
-
|
X
|
|
4 | Is informed about new and upcoming applications in the field and learns them whenever necessary. |
-
|
-
|
-
|
X
|
-
|
|
5 | Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions. |
-
|
-
|
-
|
-
|
X
|
|
6 | Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs. |
-
|
-
|
-
|
-
|
X
|
|
7 | Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process. |
-
|
X
|
-
|
-
|
-
|
|
8 | Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility. |
-
|
-
|
X
|
-
|
-
|
|
9 | Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale. |
-
|
-
|
X
|
-
|
-
|
|
10 | Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form. |
-
|
-
|
X
|
-
|
-
|
|
11 | Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications. |
-
|
X
|
-
|
-
|
-
|
|
12 | Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. |
-
|
X
|
-
|
-
|
-
|
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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