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| Detailed information |
| Original study plan |
Bachelor's programme Technical Mathematics 2025W |
| Learning Outcomes |
Competences |
- Students are acquainted with the mathematical, logical and statistical foundations of expert and data based fuzzy systems.
- Students are able to formalize and model rule based fuzzy systems.
- Students know about and are able to apply methods for creating data based static and dynamic (evolving) fuzzy systems.
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| Skills |
Knowledge |
- Appropriate modeling of linguistic terms by appropriate fuzzy sets (K6)
- Knowing and proving properties of t-norms, t-conorms, negation and implcations (K3, K4)
- Developing a rule base for an application setting (K6)
- Knowing and explaining different fuzzy inference schemata (K2, K3)
- Designing and executing exemplary Mamdani und Tagaki-Sugeno-Kang fuzzy systems (K1, K5, K6)
- Proving mathematical properties of fuzzy systems (K1, K2)
- Knowing and applying clusteringtechniques for obtaining fuzzy sets and a rule base along with their evaluation (K1, K3, K5)
- Analyzing, interpreting and developing strategies for further evolving given examples of data based fuzzy systems (K4, K5, K6)
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- Types of fuzzy sets (triangular, trapezoidal, Gaussian)
- Semantic models for many-valued conjunction, disjunction, negation and implication
- Fuzzy inference schemes (assignment, deductive approach)
- Mamdani und Tagaki-Sugeno-Kang fuzzy
- Selected defuzzification strategies
- Clustering techniques like fuzzy c-means, Gustafson-Kessel models for determining data based fuzzy systems
- Evolving fuzzy systems: strategies for local and global parameter updating and for structure evolving
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| Criteria for evaluation |
written examination
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| Methods |
Blackboard presentation and slides.
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| Language |
English and French |
| Study material |
- R. Kruse, J. Gebhard, and F. Klawonn. Foundations of Fuzzy Systems. J. Wiley&Sons, Chicester, 1994.
- E. Lughofer. Evolving Fuzzy Systems. Methodologies, Advance Concepts and Applications. Springer, Berlin/Heidelberg, 2011
- R. Kruse, S. Mostaghim, C. Borgelt, C. Braune, M. Steinbrecher. Computational Intelligence - A Methodological Introduction, 3rd edition, Springer-Verlag, Berlin/Heidelberg, 2022
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| Changing subject? |
No |
| Corresponding lecture |
(*)TM1WMVOFUZC: VO Fuzzy Control (3 ECTS)
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| Earlier variants |
They also cover the requirements of the curriculum (from - to)
201WIMSFUSV18: VL Fuzzy Systems (2018W-2025S)
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