- 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.
- Deputy Head of Department (Area Chair) of Operations Management, Information Systems, Strategy, Innovation, and Entrepreneurship
- Global DBA Director, Durham-emlyon
- Professor and Chair in Business Information Systems and Analytics, Durham University Business School
- Editor-in-Chief Journal of the Operational Research Society
- Senior Common Room Member University College Durham (Castle) and St Mary’s College
- Director, Institute for Hazard, risk, and Resilience (IHRR) Forecasting Laboratory
Dr. Konstantinos (Kostas) Nikolopoulos is the Professor in Business Information Systems and Analytics at Durham University Business School.
Dr. Nikolopoulos studied Electrical and Computer Engineering at the National Technical University of Athens (ΕΜΠ) in his native Greece (D.Eng. 2002, Dipl. Eng. 1997). He further completed the International Teachers Programme (ITP) at Kellogg School of Management at Northwestern University (2011). His research interests are Forecasting, Analytics, Information Systems, and Operations.
Dr. Nikolopoulos was Professor of Business Analytics/Decision Sciences at Bangor University for a full decade, and completed three tenures as the College Director of Research (Associate Dean for Research & Impact) for the College of Business, Law, Education, and Social Sciences (2011-2018) in charge of the REF2014 submission for the Business and the Law school. Before that, he was Lecturer and Senior Lecturer in Decision Sciences at the University of Manchester, a Senior Research Associate at Lancaster University and the CTO of the Forecasting and Strategy Unit (www.fsu.gr) in the Electrical and Computer Engineering Department of the National Technical University of Athens (1996-2004). He has also held fixed-term teaching and academic appointments in the Indian School of Business, Korea University, Univerity of the Peloponnese, Hellenic International University, RWTH Aachen, Lille 2, and more recently in Kedge Business School.
Professor Nikolopoulos is an Associate Editor of Oxford IMA "Journal of Management Mathematics" and the "Supply Chain Forum, an International Journal" (Taylor & Francis); he is also the Section Editor-In-Chief for the "Forecasting in Economics and Management" section in the MDPI open access journal "Forecasting".
Professor Nikolopoulos is currently Co-Investigator in two major research grants for a) the GCRF; South Asia Self Harm research capability building initiative (SASHI) project funded by the Medical Research Council in UK (2017-2021), http://sashi.bangor.ac.uk/., and b) the H2020-FETPROACT; Radioactivity Monitoring in Ocean Ecosystems (RAMONES) funded by the EU (2021-2025). In the past he has succesfully bid as PI for more than £0.5M of research grants through the forecasting laboratory (forLAB) he founded and directed in Prifysgol Bangor University in Wales, UK.
Professor Nikolopoulos' work has been consistently appearing in the International Journal of Forecasting (29 outputs) but also in journals for broader audiences including the Journal of Operations Management, the European Journal of Operational Research, and the Journal of Computer Information Systems.
Title of the presentation:
In the light of the frantic welcome of AI, and all the changes it will bring, we are revisiting the long-standing battle, of on the one hand the Computer, the machine, the artificial brain, the AI… and on the other hand, the real Brain, the natural human intelligence, HI. We do so in the context of forecasting in business, finance, and economics and we highlight the last few areas where the human brain can bring true excellence, and we also translate this into lessons for implementation and (information) systems designers and developers. We do also discuss issues of accountability of forecasting errors.
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.
