Course details

# Mathematical Foundations of Fuzzy Logic

IMF Acad. year 2017/2018 Winter semester 5 credits

At the beginning of semester, students choose from the supplied topics. On the weekly seminars, they present the topics and discuss about them. The final seminar is for assesment of students' performance.

Guarantor

Language of instruction

Czech

Completion

Classified Credit

Time span

26 hrs exercises, 26 hrs projects

Assessment points

30 exercises, 70 projects

Department

Instructor

Subject specific learning outcomes and competences

Successfull students will gain deep knowledge of the selected area of mathematics (depending on the seminar group), and ability to present the studied area and solve problems within it.

Generic learning outcomes and competences

The ability to understand advanced mathematical texts, the ability to design nontrivial mathematical proofs.

Learning objectives

To extend an area of mathematical knowledge with an emphasis of solution searchings and mathematical problems proofs.

Prerequisites

Prerequisite kwnowledge and skills

Knowledge of "IDA - Discrete Mathematics" and "IMA - Mathematical Analysis" courses.

Study literature

1. Alsina, C., Frank, M.J., Schweizer, B., Assocative functions: Triangular Norms and Copulas, World Scientific Publishing Company, 2006
2. Kolesárová, A., Kováčová, M., Fuzzy množiny a ich aplikácie, STU v Bratislave, 2004

Fundamental literature

1. Alsina, C., Frank, M.J., Schweizer, B., Assocative functions: Triangular Norms and Copulas, World Scientific Publishing Company, 2006
2. Baczynski, M., Jayaram, B., Fuzzy implications, Studies in Fuzziness and Soft Computing, Vol. 231, 2008
3. Carlsson, Ch., Fullér, R., Fuzzy reasoning in decision making and optimization, Studies in Fuzziness and Soft Computing, Vol. 82, 2002
4. Kolesárová, A., Kováčová, M., Fuzzy množiny a ich aplikácie, STU v Bratislave, 2004

Syllabus of numerical exercises

1. From classical logic to fuzzy logic
2. Modelling of vague concepts via fuzzy sets
3. Basic operations on fuzzy sets
4. Principle of extensionality
5. Triangular norms, basic notions, algebraic properties
6. Triangular norms, constructions, generators
7. Triangular conorms, basic notions and properties
8. Negation in fuzzy logic
9. Implications in fuzzy logic
10. Aggregation operators, basic properties
11. Aggregation operators, applications
12. Fuzzy relations
13. Fuzzy preference structures

Syllabus - others, projects and individual work of students

1. Triangular norms, class of třída archimedean t-norms
2. Triangular norms, construction of continuous t-norms
3. Triangular norms, construction of non-continuous t-norms
4. Triangular conorms
5. Fuzzy negations and their properties
6. Implications in fuzzy logic
7. Aggregation operators, averaging operators
8. Aggregation operators, applications
9. Fuzzy relations, similarity, fuzzy equality
10. Fuzzy preference structures

Progress assessment

Active participation in the exercises: 30 points.
Projects: 70 points.

Controlled instruction

Active participation in the exercises (group problem solving, evaluation of the ten exercises): 30 points.
Projects: group  presentation, 70 points.

Exam prerequisites

Students have to get at least 50 points during the semester.

Course inclusion in study plans

• Programme IT-BC-3, field BIT, any year of study, Elective
• Programme IT-BC-3, field BIT, 2nd year of study, Elective