COURSE UNIT TITLE

: FUZZY SYSTEMS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5072 FUZZY SYSTEMS ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR NESLIHAN AVCU

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING NON -THESIS (EVENING PROGRAM)
ELECTRICAL AND ELECTRONICS ENGINEERING
ELECTRICAL AND ELECTRONICS ENGINEERING
ELECTRICAL AND ELECTRONICS ENGINEERING

Course Objective

This course aims to introduce the basics of fuzzy sets, fuzzy logic and fuzzy decision making.

Learning Outcomes of the Course Unit

1   Be able to understand the basics of fuzzy sets and fuzzy logic
2   Be able to perform operations on fuzzy sets
3   Be able to apply basic knowledge of fuzzy information representation and processing
4   Be able to apply fuzzy logic and approximate reasoning
5   Be able to understand the notion of fuzzy rule base, the fuzzifiers and defuzzifiers
6   Be able to design a fuzzy system from input output data

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction-What are fuzzy systems
2 Fuzzy Sets and Basic Operations on Fuzzy Sets-I
3 Fuzzy Sets and Basic Operations on Fuzzy Sets-II
4 Further Operations on Fuzzy Sets
5 Fuzzy Relations and the Extension Principle
6 Linguistic Variables and Fuzzy If-Then Rules
7 Fuzzy Logic and Approximate Reasoning
8 Fuzzy Rule Base and Fuzzy Inference Engine-I
9 Fuzzy Rule Base and Fuzzy Inference Engine-II
10 Midterm examination
11 Fuzzifiers and Defuzzifiers
12 Fuzzy Systems as Nonlinear Mappings
13 Approximation Properties of Fuzzy Systems
14 Design of Fuzzy Systems From Input-Output Data

Recomended or Required Reading

Textbook(s): A Course in Fuzzy Systems and Control, Li-Xin Wang, Prentice-Hall International Inc.

Supplementary Book(s):
Fuzzy Logic with Engineering Applications, Timothy j. Ross, 3/e, 2010, John Wiley.
G. Chen and T. T. Pham, Introduction to Fuzzy Systems, CRC Press, 2006

Planned Learning Activities and Teaching Methods

A series of lectures on course materials will be given using PowerPoint presentations and blackboard

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 PRJ PROJECT
2 MTE MIDTERM EXAM
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE PRJ * 0.30 + MTE * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) PRJ * 0.30 + MTE * 0.30 + RST * 0.40


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

Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes will be evaluated by examinations and assignments.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

neslihan.avcu@deu.edu.tr

Tel: 0 232 301 7681

Office Hours

on Wednesday, between 14:50-16:30

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 5 65
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Preparing assignments 1 20 20
Preparing presentations 1 28 28
Final 1 3 3
Midterm 1 3 3
TOTAL WORKLOAD (hours) 193

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.11
LO.2112
LO.3112
LO.4112
LO.51
LO.612