Automatic fuzzy model generation from sample data is relatively well supported by scientifical articles and commercial software products (e.g. Matlab’s Fuzzy Logic Toolbox) in case of low number of dimensions and small data samples. However, with the increase of the dimensionality of the problems (e.g. more than 5-7 input dimensions) and the increase of the amount of the available sample data (e.g. more than 200 samples) the determination of the optimal system parameters can become extremely hard and time consuming.
Through this project, we aim to develop new techniques that enable us to efficiently create and optimize fuzzy systems for cases when the number of input dimensions exceeds 25 and the available data can contain more than 10 000 samples. The research may include deep learning like techniques, nature inspired optimization techniques, data analysis (e.g. ANOVA, SVD), as well as fuzzy rule interpolation.
Jelentkezési határidő: 2021-02-01
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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