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Fuzzy GUHA
Ralbovský, Martin ; Rauch, Jan (advisor) ; Svátek, Vojtěch (referee) ; Holeňa, Martin (referee) ; Vojtáš, Peter (referee)
The GUHA method is one of the oldest methods of exploratory data analysis, which is regarded as part of the data mining or knowledge discovery in databases (KDD) scienti_c area. Unlike many other methods of data mining, the GUHA method has firm theoretical foundations in logic and statistics. In scope of the method, finding interesting knowledge corresponds to finding special formulas in satisfactory rich logical calculus, which is called observational calculus. The main topic of the thesis is application of the "fuzzy paradigm" to the GUHA method By the term "fuzzy paradigm" we mean approaches that use many-valued membership degrees or truth values, namely fuzzy set theory and fuzzy logic. The thesis does not aim to cover all the aspects of this application, it emphasises mainly on: - Association rules as the most prevalent type of formulas mined by the GUHA method - Usage of fuzzy data - Logical aspects of fuzzy association rules mining - Comparison of the GUHA theory to the mainstream fuzzy association rules - Implementation of the theory using the bit string approach The thesis throughoutly elaborates the theory of fuzzy association rules, both using the theoretical apparatus of fuzzy set theory and fuzzy logic. Fuzzy set theory is used mainly to compare the GUHA method to existing mainstream approaches to formalize fuzzy association rules, which were studied in detail. Fuzzy logic is used to define novel class of logical calculi called logical calculi of fuzzy association rules (LCFAR) for logical representation of fuzzy association rules. The problem of existence of deduction rules in LCFAR is dealt in depth. Suitable part of the proposed theory is implemented in the Ferda system using the bit string approach. In the approach, characteristics of examined objects are represented as strings of bits, which in the crisp case enables efficient computation. In order to maintain this feature also in the fuzzy case, a profound low level testing of data structures and algoritms for fuzzy bit strings have been carried out as a part of the thesis.
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Two Connections between Epistemic and Fuzzy Logics
Běhounek, Libor
Two possible connections between epistemic and fuzzy logics are studied. Epistemic fuzzy logic as a kind of modal logic studies the reasoning of agents about fuzzy propositions; problems of such a synthesis caused by the invalidity of the axiom K are hinted at. Another direction is to found epistemic on fuzzy logic; the paper sketches the way how representing feasible knowledge as a fuzzy modality eliminated the logical omniscience paradox.
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Automatické dokazování ve fuzzy logikách
Cintula, Petr ; Navara, M.
Computer algebra allows to perform many operations which were considered difficult, e.g., factorization, integration, symbolic solution of ODEs, etc. Logical operations are not always implemented. E.g., Maple 9 has a package LOGIC which was missing in several preceding versions. Except for packages for fuzzy control, there seems to be no professional software for fuzzy logical tasks. Here we summarize current situation in computer algebra support of testing tautologies in fuzzy logics.
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Slabě implikační predikátové fuzzy logiky
Cintula, Petr
There are two classes of propositional logics related to the area of mathematical fuzzy logics proposed in work of the author (see also joint paper by the author and Libor Běhounek where philosophical, methodological, and pragmatical reasons for introducing these two classes appear.) After we recall same basic definitions we turn our attention to the first-order variants of these two classes of logics. The results presented here are mainly from the author's thesis and his upcoming paper. Because of the lack of space we present the basic definitions and theorems only and we completely disregard the important concept of Baaz delta.
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Consistency of fuzzy logic theories of inference systems
Havlíček, Petr ; Ivánek, Jiří (advisor) ; Jirků, Petr (referee)
This thesis focus on consistency of a specific class of fuzzy logic theories that represent certain inference system. This class of theories is defined as theories containing especially so called special axioms representing rules of modeled inference system and evaluated set of formulas representing case data. Functional approach is used to develop three popular fuzzy calculi: the Gödel logic, Łukasiewicz logic and product logic. As a language it is used the language of first order propositional fuzzy logic with valuation. To check consistency we use the concept of inconsistency degree and in Łukasiewicz logic also the principle of polar index. The concept of consistency degree is also described, but not used. Simple algorithm is developed to check consistency of theory upon the basis of inconsistency degree principle. A method of use of polar index is also described and illustrated. For each fuzzy theory a term of corresponding classical theory is defined. Then consistency of fuzzy theories and their corresponding classical theories are compared. The results of comparison are presented on the example of the ad-hoc created diagnostic inference system MEDSYS II. In the end the relation between consistency of fuzzy theory of inference system and it's corresponding theory is introduced for all three used calculi and both contradiction concepts.
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