COURSE UNIT TITLE

: INTELLIGENT SYSTEM APPLICATIONS USING FUZZY LOGIC

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSC 5046 INTELLIGENT SYSTEM APPLICATIONS USING FUZZY LOGIC ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR EFENDI NASIBOĞLU

Offered to

Ph.D. in Computer Science (English)
Computer Science
Artificial Intelligence and Intelligent Systems

Course Objective

Students will gain the ability to create various system designs with the use of fuzzy logic and perform them with software tools.

Learning Outcomes of the Course Unit

1   Understanding of theoretical and practical knowledge for system modeling.
2   Understanding the mathematical techniques required to process fuzzy information in the modeling process.
3   Understanding fuzzy knowledgeable decision techniques.
4   Understanding the application tools used in fuzzy systems.
5   Ability to develop practical fuzzy system development

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction
2 Fuzzy Logic in Power Plants
3 Fuzzy Logic Applications in Data Mining
4 Fuzzy Logic in Image Processing
5 Project presentations
6 Fuzzy Logic in Biomedicine
7 Fuzzy Logic in Industrial Applications
8 Fuzzy Logic in Industrial Applications (Cont)
9 Project presentations
10 Fuzzy Logic in Automotive Applications
11 Project presentations
12 Application of Fuzzy Expert System
13 Fuzzy Logic in Control
14 Final presentations

Recomended or Required Reading

Textbook(s):
Sivanandam S.N., Deepa S.N., Sumathi S. (2007). Introduction to Fuzzy Logic Using MATLAB., Springer
Supplementary Book(s):
Jang, J., Sun C., Mizutani E. Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall, 1997.

Planned Learning Activities and Teaching Methods

The course will be taught in the form of expression, classroom presentation and discussion. In addition to the course taught, group presentations will be prepared and presented as controversial sessions. In some weeks of the course, the results of the given homework will be discussed and discussed.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 PRJ PROJECT
2 FCG FINAL COURSE GRADE PRJ * 1


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

efendi.nasibov@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 4 56
Preparing assignments 4 20 80
Preparing presentations 4 5 20
TOTAL WORKLOAD (hours) 198

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.155555
LO.255555
LO.355555
LO.455555
LO.555555