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Start Over Subject many-valued logic

2. An alternative approach to the ŁII logic

Creator:
Cintula, Petr
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
fuzzy logic and many-valued logic
Language:
English
Description:
The ŁII and ŁII1/2 logics were introduced by Godo, Esteva and Montagna in [4] and further developed in my work [2]. These types of logic unite many other known propositional and predicate logics, including the three mainly investigated ones (Godel, Product and Łukasiewicz logic). The aim of this paper is to show a tight connection between the ŁII logic and the product involutive logic. This logic was introduced by Esteva, Godo, Hájek and Navara in their paper [3]. We will see that all the connectives of the ŁII logic are definable from the connectives of this logic. In addition we show that the ŁII logic is an schernatic extension of this logic by a single axiom. We also make some simplification of the axiomatic system of this logic.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

3. Rational Łukasiewicz logic and DMV-algebras

Creator:
Gerla, Brunella
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
many-valued logic, fuzzy logic, Rational Łukasiewicz logic, DMV-algebras, completeness, and computational complexity
Language:
English
Description:
In this paper we present some results concerning the variety of divisible MV-algebras. Any free divisible MV-algebra is an algebra of continuous piecewise linear functions with rational coefficients. Correspondingly, the Rational Łukasiewicz logic is defined and its tautology problem is shown to be co-NP-complete.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

4. Short term prediction of highway travel time using GUHA data mining method

Creator:
Coufal, David and Turunen, Esko
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
data mining and many-valued logic
Language:
English
Description:
We show that prediction of travel time on a 28-km long highway section based on on-line travel time measurements with video is practicable by a data mining method. We introduce a new prediction model, a result of the GUHA style data mining analysis and tlie Total Fuzzy Similarity method. Comparing the results with the existing Traficon model, oiir model improves the travel time class prediction. The results obtained by our method are comparable to the MLP neural network model, too.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public