CLICK HERE FOR THE COURSE SYLLABUS (.pdf)


COURSE INTRODUCTION AND APPLICATION INFORMATION

 
Course Name
Code
Semester
Theory
(hour/week)
Application/Laboratory
(hour/week)
Local Credits
ECTS
Fuzzy Set Theory and Its Applications
MATH 655
Fall/Spring
3
0
3
7.5

Prerequisites
None

Course Language
English
Course Type
Elective
Course Level
Third Cycle
Course Coordinator -
Course Lecturer(s)
Course Assistants -
Course Objectives Fuzzy Set Theory is a tool that can be applied to ambiguous, complicated, complex, or nonlinear systems or problems, which cannot easily solved by classical set theory or probability theory. In this course the fundamental of fuzzy set theory and fuzzy logic will be introduce. In addition, this course also introduces applications of fuzzy logic in several areas such as fuzzy control and fuzzy decision making
Course Learning Outcomes The students who succeeded in this course;
  • will be able to interpret systems using fundamentals of fuzzy set theory.
  • will be able to solve decision problems using Fuzzy logic.
  • will be able to analyze Fuzzy control systems.
  • will be able to introduce new fuzzy systems.
  • will be able to express the relationship between Fuzzy set theory and probability theory.
Course Content This course aims to cover the fundemental fuzzy theory and its applications of fuzzy logic.

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Fuzzy Sets Basic Definitions H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
2 Extensions H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996..
3 Fuzzy Measures and Measures of Fuzziness H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
4 The Extension Principle and Applications H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
5 Fuzzy Relations and Fuzzy Graphs H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
6 Fuzzy Analysis H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
7 Possibility Theory, Probability Theory, and Fuzzy Set Theory H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
8 Fuzzy Logic H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
9 Approximate Reasoning H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
10 Fuzzy Sets and Expert Systems H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
11 Fuzzy Control H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
12 Fuzzy Data Analysis H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
13 Decision Making in Fuzzy Environments H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
14 Fuzzy Set Models in Operations Research H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
15 Empirical Research in Fuzzy Set Theory H.J. Zimmermann,”Fuzzy set theory and its applications”, 3 ed. Norwell, MA:Kluwer, 1996.
16 Review of the Semester  

 

SOURCES

Course Notes / Textbooks The extracts above and exercises will be given.
References T. Terano, K. Asai, and M. Sugeno, Fuzzy systems theory and its applications,1 ed. San Diego, CA: Academic press, 1992, T. J. Ross, Fuzzy logic with engineering applications, 1 ed. New York, NY: McGrawHill, 1995.

 

EVALUATION SYSTEM

Semester Requirements Number Percentage of Grade
Attendance/Participation
Laboratory
Application
Field Work
Special Course Internship (Work Placement)
Quizzes/Studio Critics
Homework Assignments
Presentation/Jury
Project
1
30
Seminar/Workshop
Midterms/Oral Exams
1
30
Final/Oral Exam
1
40
Total

PERCENTAGE OF SEMESTER WORK
60
PERCENTAGE OF FINAL WORK
40
Total

 

COURSE CATEGORY

Course Category

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

 

THE RELATIONSHIP BETWEEN COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS

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

To develop and deepen his/her knowledge on theories of mathematics and statistics and their applications in level of expertise, and to obtain unique definitions which bring innovations to the area, based on master level competencies,

X
2

To have the ability of original, independent and critical thinking in Mathematics and Statistics and to be able to develop theoretical concepts,

X
3

To have the ability of defining and verifying problems in Mathematics and Statistics,

X
4

With an interdisciplinary approach, to be able to apply theoretical and applied methods of mathematics and statistics in analyzing and solving new problems and to be able to discover his/her own potentials with respect to the application,

X
5

In nearly every fields that mathematics and statistics are used, to be able to execute, conclude and report a research, which requires expertise, independently,

X
6

To be able to evaluate and renew his/her abilities and knowledge acquired in the field of Applied Mathematics and Statistics with critical approach, and to be able to analyze, synthesize and evaluate complex thoughts in a critical way,

X
7

To be able to convey his/her analyses and methods in the field of Applied Mathematics and Statistics to the experts in a scientific way,

X
8

To be able to use national and international academic resources (English) efficiently, to update his/her knowledge, to communicate with his/her native and foreign colleagues easily, to follow the literature periodically, to contribute scientific meetings held in his/her own field and other fields systematically as written, oral and visual.

X
9

To be familiar with computer software commonly used in the fields of Applied Mathematics and Statistics and to be able to use at least two of them efficiently,

X
10

To contribute the transformation process of his/her own society into an information society and the sustainability of this process by introducing scientific, technological, social and cultural advances in the fields of Applied Mathematics and Statistics,

X
11

As having rich cultural background and social sensitivity with a global perspective, to be able to evaluate all processes efficiently, to be able to contribute the solutions of social, scientific, cultural and ethical problems and to support the development of these values,

X
12

As being competent in abstract thinking, to be able to connect abstract events to concrete events and to transfer solutions, to analyze results with scientific methods by designing experiment and collecting data and to interpret them,

X
13

To be able to produce strategies, policies and plans about systems and topics in which mathematics and statistics are used and to be able to interpret and develop results,

X
14

To be able to evaluate, argue and analyze prominent persons, events and phenomena, which play an important role in the development and combination of the fields of Mathematics and Statistics, within the perspective of the development of other fields of science,

X
15

In Applied Mathematics and Statistics, to be able to sustain scientific work as an individual or a group, to be effective in all phases of an independent work, to participate decision-making process and to make and execute necessary planning within an effective time schedule.

X

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

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
16
3
Laboratory
Application
Special Course Internship (Work Placement)
Field Work
Study Hours Out of Class
16
5
Presentations / Seminar
Project
1
25
Homework Assignments
Quizzes
Midterms / Oral Exams
1
32
Final / Oral Exam
1
40
    Total Workload

CLICK HERE FOR THE COURSE SYLLABUS (.pdf)

 
 

İzmir Ekonomi Üniversitesi | Sakarya Caddesi No:156, 35330 Balçova - İZMİR Tel: +90 232 279 25 25 | webmaster@ieu.edu.tr | YBS 2010