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Fundamenta Informaticae

Tytuł artykułu

Rough Truth Degrees of Formulas and Approximate Reasoning in Rough Logic

Autorzy She, Y.  He, X.  Wang, G. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
EN A propositional logic PRL for rough sets was proposed in [1]. In this paper, we initially introduce the concepts of rough (upper, lower) truth degrees on the set of formulas in PRL. Then, by grading the rough equality relations, we propose the concepts of rough (upper, lower) similarity degree. Finally, three different pseudo-metrics on the set of rough formulas are obtained, and thus an approximate reasoning mechanism is established.
Słowa kluczowe
EN rough upper truth degree   rough lower truth degree   rough similarity degree   rough pseudo-metric   approximate reasoning  
Wydawca IOS Press
Czasopismo Fundamenta Informaticae
Rocznik 2011
Tom Vol. 111, nr 2
Strony 223--239
Opis fizyczny Bibliogr. 29 poz.
autor She, Y.
autor He, X.
autor Wang, G.
[1] Banerjee, M.: Rough sets through algebraic logic. Fundamenta Informaticae, 32: 213-220, 1997.
[2] Pawlak, Z.: Rough sets. International Journal of Computer and InformationSciences 11(5): 341-356, 1982.
[3] Pawlak, Z.: Rough sets−T heoretical aspects of reasoning about data. Knowledge academic publishers, 1991.
[4] Chen, Y., Yao, Y.: A multiview approach for intelligent data analysis based on data operators. Information Sciences, 178(1): 1-20, 2008.
[5] Herbert, J., Yao, J.: Rough set model selection for practical decision making. Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD, 203-207, 2007.
[6] Grzymala-Busse, J.: Mining numerical data- A rough set approach. Transactions on Rough Sets, XI 5946: 1-13, 2010.
[7] Pawlak, Z.: Rough logic. Bull. Polish Acad. Sc. (Tech. Sc.), 35: 253-258, 1987.
[8] Orlowska, E.: Kripke semantics for knowledge representation logics. Studia Logica, XLIX: 255-272, 1990.
[9] Vakarelov, D.: A modal logic for similarity relations in Pawlak knowledge representaion systems. Fundamenta Informaticae, 15: 61-79, 1991.
[10] Vakarelov, D.: Modal logics for knowledge representation systems. T heoretical Computer Science, 90: 433-456, 1991.
[11] Duentsch, I.: A logic for rough sets. T heoretical Computer Science, 179: 427-436, 1997.
[12] Chakrabotry,M.: Rough consequence. Bull. Polish Acad. Sc.(Math.), 41(4): 299-304, 1993.
[13] Dai, J.: Logic for rough sets with rough double stone algebraic semantics. Lecture Notes in Computer Science, 3641: 141-148, 2005.
[14] Banerjee, M.: Logic for rough truth. Fundamenta Informaticae, 71(2-3): 139-151, 2006.
[15] Pagliani, P., Chakraborty,M. A geometry of approximation. Rough set theory : logic, algebra and topology of conceptual patterns. Springer, 2008.
[16] Banerjee, M.: Propositional logic from rough set theory. Transactions on Rough Sets, VI: 1-25, 2007.
[17] Wang, G., Zhou. H.: Introduction to mathematical logic and resolution principle. Science Press, Beijing& Alpha Science International Limited, Oxford, U.K, 2009.
[18] Wang, G., Zhou, H.: Quantitative logic. Information Sciences, 179: 226-247, 2009.
[19] Pavelka, J.: On fuzzy logic I, II, III, Zeitschr. Math. Logik Grund. d. Math. 25: 45-72, 119-134, 447-464, 1979.
[20] Zadeh, L.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1: 3-28, 1978.
[21] Hajek, P.: Metamathematics of Fuzzy Logic. Kluwer Academic Publishers, London, 1998.
[22] Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning, parts 1-3. Inform. Sci., 8: 199-249, 301-357; 9: 43-80, 1975.
[23] Graham, I., Jones, L.: Expert systems − knowledge, uncertainty and decision. Chapman and Hall Computing, London, 1998.
[24] Halmos, P.: Measure theory. Springer-Verlag, New York, 1955.
[25] Kelley, J.: General topology. Springer-Verlag, New York, 1955.
[26] Chakraborty,M., Banerjee, M.: Rough consequence. Bull. Polish Acad., 41(4): 299-304, 1993.
[27] Chakraborty,M.: Graded consequence: further studies. Journal of Applied Nonclassical Logic, 5:227-237, 1994.
[28] Banerjee,M.: Rough truth, consequence, consistency and belief revision. Lecture Notes in Computer Science, 3066:95-102, 2004.
[29] Munino, D.: A graded inference approach based on infinite-valued Łukasiewicz semantics. ISMV L, 252-257, 2010.
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