- Prof. Vilem Novak, University of Ostrava, Institute for Research and Applications of Fuzzy Modeling, Czech Republic
- Former director of IRAFM
- Vice-president of IFSA
- Senior member of IEEE
Prof. Vilem Novak, Ph.D., DSc. is the founder and former director of the Institute for Research and Applications of Fuzzy Modeling of the University of Ostrava, Czech Republic. The institute (established in 1996) is one of the world-renowned scientific workplaces that significantly contributed to the theory and applications of fuzzy modeling.
V. Novak obtained a PhD in mathematical logic at Charles University, Prague in 1988; DSc. (Doctor of Sciences) in computer science in the Pol- ish Academy of Sciences, Warsaw in 1995; full professor at Masaryk University, Brno in 2001. His research activities include mathematical fuzzy logic, approx- imate reasoning, mathematical modeling of linguistic semantics, fuzzy control, analysis and forecasting of time series, and various kinds of fuzzy modeling applications. He belongs among the pioneers of the fuzzy set theory.
He was general chair of the VIIth IFSA’97 World Congress, Prague and of the international conferences EUSFLAT 2007, Ostrava and EUSFLAT 2019, Prague. He is a member of the editorial boards of several scientific journals. He is often invited to give plenary talks at international conferences and give lectures in universities worldwide.
He is the author or co-author of 6 scientific monographs, two edited mono- graphs, and over 310 scientific papers with almost 9000 citations. He was awarded in the International Conference FLINS 2010 in China and obtained the title “IFSA fellow” in 2017 for his scientific achievements. He is currently the vice-president of IFSA.
Title of the presentation:
We will present special techniques of fuzzy modeling suitable for applications in time series processing, namely the Fuzzy Transform (F-transform) and selected methods of Fuzzy Natural Logic (FNL). The F-transform is applied to estimation of the trend or trend-cycle of time series, and to estimation of the slope of time series over an imprecisely specified area. Our methods are based on the decomposition of the time series into 4 components: trend, cycle, seasonal component, and random disturbances. The fuzzy transform makes it possible to find arbitrary shape of the trend or trend-cycle. It has been proved that using the F-transform, we can eliminate seasonal component and significantly reduce noise. Moreover, the computational complexity is low.
Our methods also have applications in mining information from time series. Among them, let us mention reduction of dimensionality, finding intervals of monotonous behavior and their characterization using expressions of natural language, measure of similarity between time series, or automatic summarization of knowledge about time series. We also suggest a powerful method for detection of structural breaks. The found structural breaks are also statistically tested.
We will compare our methods with traditional methods and demonstrate that they can on one hand successfully compete with them and on the other hand, both kinds of methods can be combined to increase the effectivity of the processing of time series.
Martin Wagner currently is Professor of Economics at the University of Klagenfurt, Chief Economic Advisor at the Bank of Slovenia and Fellow of the Macroeconomics and Economic Policy group at the Institute for Advanced Studies, Vienna. From October 2017 until end of 2018 he was Chief Economist of the Bank of Slovenia, being on leave from Technical University Dortmund, where we has been Professor of Econometrics and Statistics in the Faculty of Statistics of the Technical University Dortmund from 2012 until 2019. He was educated in Vienna, at the Technical University and the Institute for Advanced Studies, obtaining Diplomas in Mathematics (1995) and Economics (1998), as well as his Doctorate (2000). He obtained his Habilitation in Economics in 2007 at the University of Bern. Martin Wagner has worked at the Technical University of Vienna, the Institute for Advanced Studies in Vienna, the University of Bern and has been Professor of Econometrics and Empirical Economics at the University of Graz before his arrival in Dortmund. Visiting positions have brought him to Princeton University and the European University Institute in Florence.
His work has been published, amongst other outlets, in Journal of Econometrics, Econometric Theory, Journal of Applied Econometrics, Econometric Reviews, Econometrics, Oxford Bulletin of Economics and Statistics, Journal of Empirical Finance, Economics of Transition and Ecological Economics.
