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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BIL 3009 FUZZY LOGIC AND FUZZY SETS COMPULSORY 3 0 0 6

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR AYŞE ÖVGÜ KINAY

Offered to

Computer Science

Course Objective

The objective of the course is to provide information about fuzzy logic and fuzzy sets theory, calculations with using fuzzy sets, definition of linguistic variable and how to use in various calculations.

Learning Outcomes of the Course Unit

1   Be able to explain the differences between classical set and fuzzy set. 2   Be able to perform set operations on fuzzy sets. 3   Be able to perform arithmetical operations on fuzzy numbers. 4   Be able to to solve problems using linguistic variables. 5   Be able to interpret the systems that contains fuzziness.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Fuzzy logic principles and foundations 2 Classical and fuzzy set operators 3 Fuzzy set and its properties 4 Complement and intersection (t-norm) operators in fuzzy sets 5 Union (t-conorm) and aggregation operators in fuzzy sets 6 Extension principle 7 Fuzzy relationship concept, properties and operations 8 Review of Topics 9 Fuzzy relationship concept, properties and operations (continued) 10 Interval arithmetic and Fuzzy arithmetic 11 Fuzzy arithmetic (continued) 12 Linguistic variables 13 Linguistic variables and the concept of linguistic hedges 14 Defuzzification methods

Recomended or Required Reading

Textbook(s): Ross, T.J., Fuzzy Logic with Engineering Applications (4rd Edition), McGraw-Hill, 2016. Supplementary Book(s): Lin, C.T. and George Lee, C.S., Neural Fuzzy Systems, Prentice Hall, 1996. Guanrong Chen, and Trung Tat Pham, Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems, 2019.

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. In some weeks of the course, results of the homework given previously are discussed.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 VZ Vize 2 FN Final 3 BNS BNS VZ * 0.40 + FN * 0.60 4 BUT Bütünleme Notu 5 BBN Bütünleme Sonu Başarı Notu VZ * 0.40 + BUT * 0.60 *** 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

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

ovgu.tekin@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparation for midterm exam 1 20 20 Preparations before/after weekly lectures 14 4 56 Preparation for final exam 1 30 30 Midterm 1 1 1 Final 1 2 2 TOTAL WORKLOAD (hours) 151

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 3 5 4 LO.2 3 5 4 LO.3 3 5 5 4 4 4 LO.4 3 5 5 4 4 4 LO.5 5 5 4