MATH 437 | Course Introduction and Application Information - Department of Mathematics

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	-
National Occupation Classification	-
Course Coordinator	Prof. Dr. Gözde Yazgı TÜTÜNCÜ
Course Lecturer(s)	Profesör Dr. Gözde Yazgı TÜTÜNCÜ
Assistant(s)	Araş. Gör. Gökçe ÖZALTUN Araş. Gör. Ayşe BELER

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

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	Be able to examine the set theory problems.
2	Be able to interpret the systems which include fuzzines within the scope of fuzzy set theory .
3	Be able to combine the information of decision theory and the information of fuzzy set theory.
4	Be able to improve the proof techniques of fuzzy set theory.
5	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

Week	Subjects	Related Preparation	Learning Outcome
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

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5
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

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

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	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.		-	-	-	-	-