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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
FUZZY LOGIC APPLICATIONS BİL633 ------- 3 + 0 10

TYPE OF COURSE UNITElective Course
LEVEL OF COURSE UNITDoctorate Of Science
YEAR OF STUDY-
SEMESTER-------
NUMBER OF ECTS CREDITS ALLOCATED10
NAME OF LECTURER(S)Professor Nizami Gasilov
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) will be familiar with the main concepts of Fuzzy Set Theory such as membership degree, membership function, ?-level set, fuzzy number and with operations on fuzzy sets.
2) will be able to represent a fuzzy proposition using membership function, will be familiar with conditional fuzzy propositions and fuzzy inference methods
3) will be aware of the use of fuzzy inference methods in the design of intelligent systems, and will be familiar with fuzzy logic applications in robotics, control, etc.
MODE OF DELIVERYFace to face
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE CONTENTS
WEEKTOPICS
1st Week Introduction to the Theory of Fuzzy Sets and Fuzzy Logic.
2nd Week Operations on fuzzy sets.
3rd Week Fuzzy relations and Fuzzy implications.
4th Week The theory of approximate reasoning.
5th Week Fuzzy logic controllers and Applications of fuzzy systems.
6th Week Artificial neural networks.
7th Week The perceptron learning rule.
8th Week Midterm
9th Week The delta learning rule.
10th Week Applications of artificial neural networks.
11th Week Fuzzy neural networks and Fuzzy neurons.
12th Week Hybrid neural nets.
13th Week Fuzzy rule extraction from numerical data.
14th Week Applications of hybrid neural nets.
RECOMENDED OR REQUIRED READING1. R. Fuller (2000), Introduction to Neuro-Fuzzy Systems, Springer-Verlag Berlin Heidelberg.
2. T.J. Ross (2016), Fuzzy Logic with Engineering Applications, 4th Edition, Wiley.
3. K.H. Lee (2005), First Course on Fuzzy Theory and Applications, Springer.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Questions/Answers,Problem Solving,Report Preparation,Presentation
ASSESSMENT METHODS AND CRITERIA1 Midterm, 6 Homeworks, 1 Final Exam
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

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