FUZZY LOGIC in ENGINEERING APPLICATIONS

AIM

The basis of this course is to give the principles of "fuzzy logic", which we can call partial logic, under the symbolic expressions of mathematical equations that have been put forward with the idea of binary logic (everything has its opposite) in education. While all mathematical equations are processed with holistic variables and numerical data, in the fuzzy logic approach, it is possible to model by using verbal logic principles instead of equations.

CONTENT

This course contains; Introduction,Logical principles,Crisp logic, science, equations and numerical data,Fuzzy logic science and verbal expressions,Fuzzy rules (precident and consequent parts),Scientific variable word significance,Scientific sentence logical significance,Fuzzy sets and functions,Fuzzy arithmetics,Fuzzy implications,Fuzzy logic application in meteorology,Fuzzy logic application in climatology,Fuzzy logic application in engineering,General evaluation.

1. 1

   Solves different engineering problems by fuzzy logic principles.

   Taught by: Discussion Method, Question - Answer Technique, Brainstorming Technique, Reverse Brainstorming Technique, Cooperative Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

2. 2

   İnterpretes engineering equations.

   Taught by: Discussion Method, Question - Answer Technique, Brainstorming Technique, Reverse Brainstorming Technique · Assessed by: Traditional Written Exam, Homework

3. 3

   Solves problems by verbal thinking.

   Taught by: Discussion Method, Question - Answer Technique, Brainstorming Technique, Reverse Brainstorming Technique, Cooperative Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

4. 4

   Provides fuzzy logic inference modeling.

   Taught by: Discussion Method, Question - Answer Technique, Brainstorming Technique, Reverse Brainstorming Technique · Assessed by: Traditional Written Exam, Homework

WEEKLY PLAN

1. WEEK 1

   Introduction

   Preparation: Previewing book and lecture notes.

2. WEEK 2

   Logical principles

   Preparation: Previewing book and lecture notes.

3. WEEK 3

   Crisp logic, science, equations and numerical data

   Preparation: Previewing book and lecture notes.

4. WEEK 4

   Fuzzy logic science and verbal expressions

   Preparation: Previewing book and lecture notes.

5. WEEK 5

   Fuzzy rules (precident and consequent parts)

   Preparation: Previewing book and lecture notes.

6. WEEK 6

   Scientific variable word significance

   Preparation: Previewing book and lecture notes.

7. WEEK 7

   Scientific sentence logical significance

   Preparation: Previewing book and lecture notes.

8. WEEK 8

   Fuzzy sets and functions

   Preparation: Previewing book and lecture notes.

9. WEEK 9

   Fuzzy arithmetics

   Preparation: Previewing book and lecture notes.

10. WEEK 10

    Fuzzy implications

    Preparation: Previewing book and lecture notes.

11. WEEK 11

    Fuzzy logic application in meteorology

    Preparation: Previewing book and lecture notes.

12. WEEK 12

    Fuzzy logic application in climatology

    Preparation: Previewing book and lecture notes.

13. WEEK 13

    Fuzzy logic application in engineering

    Preparation: Previewing book and lecture notes.

14. WEEK 14

    General evaluation

    Preparation: Previewing book and lecture notes.

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

READING

• Şen, Z., (Bulanık Mantık İlkeleri ve Modelleme (Mühendislik ve Sosyal Bilimler): Su Vakfı Yayınları. Genişletilmiş 3. Baskı361 sayfa Ross, T., (1995). Fuzzy Logic with Engineering Applications. McGraw Hill Co., New York, 539 pages

TEACHING STAFF

• Prof.Dr. Zekai ŞENCOORDINATOR
• Prof.Dr. Zekai ŞEN