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Probabilistic-fuzzy knowledge-based system for managerial applications

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EN
Abstrakty
EN
The paper deals with an inference system with probabilistic-fuzzy knowledge base as a tool which can help users in analyzing complete uncertainty of real problems in the company using fuzzy sets and probability. In the mentioned system, knowledge is saved in the weighted IFTHEN fuzzy rules, where the weights constitute marginal probabilities of the fuzzy events in the antecedents and conditional probabilities of the fuzzy events in the consequents. Moreover, the paper presents a proposal of the use of fuzzy association rules as a method of automatic knowledge base extraction in the inference system. For this purpose a modification of the PF-Growth algorithm is described. A numerical example is analyzed by using wind speed prediction process. The correct estimation of wind speed, as the potential energy resource, is necessary for control of the wind turbine work and it is important for the localization process of wind turbines, production planning and estimating cost-effectiveness of such investments.
Twórcy
autor
  • Opole University of Technology, Faculty of Production Engineering and Logistics, Institute of Processes and Products Innovation, Ozimska 75, 45-370 Opole, Poland, phone: +48 77 4234035, k.rudnik@po.opole.pl
Bibliografia
  • [1] Koźmiński A.K., Management under the Uncertainty Conditions, Wydawnictwo Naukowe PWN, Warszawa 2005 (in Polish).
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  • [6] Walaszek-Babiszewska A., Fuzzy modeling of the stochastic systems, Theory, models, knowledge bases, OW Politechnika Opolska, Studia i Monografie, z. 261. Opole 2010 (in Polish).
  • [7] Walaszek-Babiszewska A., Fuzzy sets as an instrument to formalize of experts’ knowledge in computer systems, Zeszyty Naukowe Politechniki Śląskiej, Organizacja i Zarządzanie. Mat. Krajowej Konferencji Naukowej Wiedza - Informacja - Marketing, Szczyrk 2004 (in Polish).
  • [8] Walaszek-Babiszewska A., Chudzicki M., Fuzzy model for the information and decission making support system for the CFM branch company, Applied Computer Science, Vol. 2, No. 1, 2006, Decision Support Engineering, Banaszak Z., Matuszek J. (Eds.), pp. 110-121.
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  • [23] Walaszek-Babiszewska A., Błaszczyk K., A modified Apriori algorithm to generate rules for inference system with probabilistic-fuzzy knowledge base, 7th Int. Workshop on Advanced Control and Diagnosis 19–20 November 2009, Zielona Góra, CD-ROM.
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  • [31] Aspects of wind energy, Baza danych odnawialnych źródeł energii województwa podkarpackiego, http://www.baza-oze.pl (in Polish).
  • [32] Methods for assessing wind energy resources, Baza danych odnawialnych źródeł energii województwa podkarpackiego, http://www.baza-oze.pl (in Polish).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAR0-0066-0006
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