FACULTY OF ARTS AND SCIENCES

Department of Mathematics

MATH 437 | Course Introduction and Application Information

Course Name
Fuzzy Set Theory
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
MATH 437
Fall/Spring
3
0
3
6

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery face to face
Teaching Methods and Techniques of the Course -
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;
  • Be able to examine the set theory problems.
  • Be able to interpret the systems which include fuzzines within the scope of fuzzy set theory .
  • Be able to combine the information of decision theory and the information of fuzzy set theory.
  • Be able to improve the proof techniques of fuzzy set theory.
  • Be able to solve problems that include uncertainty with using fuzzy set theory.
Course Description The course covers basic concepts and applications of Fuzzy Set Theory.

 



Course Category

Core Courses
X
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Fuzzy sets, basic definitions G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
2 Fuzzy sets, basic definitions G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
3 Fuzzy measures and fuzziness measurements G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
4 Fuzzy measures and fuzziness measurements G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
5 Fuzzy relations and fuzzy graphics G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
6 Fuzzy relations and fuzzy graphics G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
7 Possibility theory, probability theory and fuzzy set theory G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
8 Possibility theory, probability theory and fuzzy set theory G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
9 Fuzzy logic G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
10 Midterm
11 Decision makig in fuzzy environment G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
12 Decision makig in fuzzy environment G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
13 Decision makig in fuzzy environment G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
14 Decision makig in fuzzy environment G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845
15 Semester Review
16 Final Exam

 

Course Notes/Textbooks

G.J. Klir, T.A. Folger, "Fuzzy Sets, Uncertainity, and Information" Prentice Hall, 1st Edition, 1988. ISBN-13: 978-0133459845

Suggested Readings/Materials

T.J. Ross, ''Fuzzy Logic with Engineering Applications'', Wiley, 3rd Edition,2010. ISBN-13: 978-0470743768

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
1
20
Project
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
3
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

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
14
4
56
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
1
20
20
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
24
24
Final Exam
1
32
32
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to have a grasp of basic mathematics, applied mathematics or theories and applications of statistics.

X
2

To be able to use advanced theoretical and applied knowledge, interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the fields of mathematics or statistics.

X
3

To be able to apply mathematics or statistics in real life phenomena with interdisciplinary approach and discover their potentials.

X
4

To be able to evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach and develop positive attitude towards lifelong learning.

5

To be able to share the ideas and solution proposals to problems on issues in the field with professionals, non-professionals.

6

To be able to take responsibility both as a team member or individual in order to solve unexpected complex problems faced within the implementations in the field, planning and managing activities towards the development of subordinates in the framework of a project.

7

To be able to use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge.

8

To be able to act in accordance with social, scientific, cultural and ethical values on the stages of gathering, implementation and release of the results of data related to the field.

9

To be able to possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also environmental protection, worker's health and security.

10

To be able to connect concrete events and transfer solutions, collect data, analyze and interpret results using scientific methods and having a way of abstract thinking.

X
11

To be able to collect data in the areas of Mathematics or Statistics and communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To be able to relate the knowledge accumulated throughout the human history to their field of expertise.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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