Replaces the course CS38A0060 and can not be included in the same degree.
M.Sc. (Econ & Bus. Adm.) 2
|Teacher(s) in Charge
Professor D.Sc. (Tech.), Pasi Luukka
By the end of the course student will be able to
- understand basic mathematical concepts related to fuzzy set theory and fuzzy logic
- model uncertain concepts using fuzzy set theory
- construct fuzzy models
- deduce meaningful information from fuzzy models
The course consists of basics of fuzzy set theory, algebras of fuzzy sets, fuzzy quantities, logical aspects of fuzzy sets, operations of fuzzy sets, fuzzy relations, aggregation operators, common fuzzy inference systems, including Mamdani's, Larsen's and Tsukamoto inference and Sugeno model.
Lectures 14 h, demolecture videos 7 h, exercises 14 h, 1st period. Lectures 14 h, demolecture videos 7 h, exercises 14 h, 2nd period. Independent study 90 h. Written examination. Total workload 160 h.
|Examination in Examination schedule (Yes/No)
|Examination in Moodle (Yes/No)
Yes (edit 30.3.2020)
|Examination in Exam (Yes/No)
|Assessment scale and assessment methods
0-5, examination 100 %. Moodle exam: pass-fail (edit. 30.3.2020)
Klir, G., Yuan, B.: Fuzzy Sets and Fuzzy Logic. Theory and Applications, Prentice Hall, 1995.
Fullér, R.: Introduction to Neuro-Fuzzy Systems, Physica-Verlag, 2000.
Ross, T.: Fuzzy Logic with Engineering Applications, Wiley, 2017.
Passino, K.M., Yurkovich, S.: Fuzzy control, Addison Wesley, 1998.
Bachelor level mathematics courses:
BM20A6700 Matematiikka I, osa A , BM20A6800 Matematiikka II, osa A, BM20A6900 Matematiikka III
Experience in programming or using mathematical software required:
BM20A4301 Johdatus tekniseen laskentaan or BM20A5001 Principles of Technical Computing
|Number of exercise groups where enrollment is in WebOodi (Number/Leave empty)
|Places for exchange-students? (Yes, number/No)
|Places for Open University Students?(Yes, number/No)