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Tytuł artykułu

A Graded Meaning of Formulas in Approximation Spaces

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The aim of the paper is to introduce degrees of satisfiability as well as a graded form of the meaning of formulas and their sets in the approximation space framework.
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159--172
Opis fizyczny
Bibliogr 33 poz.
Twórcy
Bibliografia
  • [1] Chakraborty. M. K.: Use of fuzzy set theory in introducing graded consequence in multiple-valued logic. Fuzzy Logic in Knowledge-Based Systems, Decision and Control (M. M. Gupta. T. Yamakawa. Eds.). Elsevier Science Publishers В. V. (North-Holland), 1988. 247-257.
  • [2] Chakraborty, M. K.: Graded consequence: Further studies. Journal of Applied Non-Classical Logics, 5(2), 1995,127-137.
  • [3] Chakraborty, M. K., Banerjee, M.: Rough consequence, Bull. Polish Acad. Sei. Math., 41(4), 1993. 299-304.
  • [4] Chakraborty. M. K., Basu. S.: Approximate reasoning methods in vagueness: Graded and rough consequences, vol. 29/95 of ICS Research Report. Institute of Computer Science, Warsaw University of Technology, Warsaw. 1995.
  • [5] Chakraborty. M. K., Basu, S.: Graded consequence and some metalogical notions generalized, Fundamenta Informaticae, 32(3-4), 1997/1998, 299-3) 1.
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  • [7] Gomolińska, A.: A comparative study of some generalized rough approximations, Fundamenta Informaticae, 51(1-2), 2002, 103-119.
  • [8] Gomolińska. A.: A graded meaning of formulas and their sets in generalized approximation spaces. Proc. Int. Workshop on Concurrency. Specification and Programming (CS&P'2003), Czarna, Poland, 2003, September 25-27 (L. Czaja. Ed.), Warsaw University, 2003. ISBN 83-88374-71-0. 157-170.
  • [9] Inuiguchi. M., Tanino, Т.: On rough sets under generalized equivalence relations. Bull. Int. Rough Set Society, 5(1-2), 2001, 167-171, ISSN 1346-0013.
  • [10] Komorowski, J., Pawlak. Z., Polkowski. L., Skowron, A.: Rough sets: A tutorial, Rough-Fuzzy Hybridization: A New Trend in Decision Making (S. K. Pal, A. Skowron, Eds.), Springer-Verlag, Singapore, 1999, 3-98.
  • [11] Leśniewski. S.: Foundations of the general set theory 1 (in Polish). Works of the Polish Scientific Circle. 2, 1916. (see also Stanisław Leśniewski Collected Works (S. J. Surma et al., Eds.), Kluwer Acad. Publ., Dordrecht, 128-173, 1992).
  • [12] Lin. T. Y.: Granular computing: Fuzzy logic and rough sets. Computing with Words in Information/Intelligent Systems (L. A. Zadeh, J. Kacprzyk, Eds.), vol. 1, Physica-Verlag, Heidelberg, 1999, 183-200.
  • [13] Lukasiewicz, J.: Die logischen Grundlagen der Wahrscheinlichkeitsrechnung, Jan Lukasiewicz – Selected Works (L. Borkowski. Ed.), North Holland Publ., Polish Scientific Publ., Amsterdam London Warsaw, 1970. 16-63, (originally published in Kraków, 1913).
  • [14] Nguyen, S. H., Skowron. A., Stepaniuk. J.: Granular computing. A rough set approach. J. Comput. Intelligence, 17(3), 2001,514-544.
  • [15] Pawlak. Z.: Rough sets. Int. J. Computer and Information Sciences, 11. 1982, 341-356.
  • [16] Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data, Kluwer Acad. Publ., Dordrecht. 1991.
  • [17] Pawlak, Z., Skowron, A.: Rough membership functions, Fuzzy Logic for the Management of Uncertainty (L. A. Zadeh, J. Kacprzyk, Eds.), John Wiley & Sons, New York, 1994. 251-271.
  • [18] Polkowski. L., Skowron. A.: Rough mereology: A new paradigm for approximate reasoning. Int. J. Approximated Reasoning. 15(4), 1996,333-365.
  • [19] Polkowski. L., Skowron. A.: Rough mereological approach - A survey, Bull. Int. Rough Set Society, 2(1), 1998, 1-13.
  • [20] Polkowski. L., Skowron, A., Eds.: Rough Sets in Knowledge Discovery, vol. 1-2, Physica-Verlag, Heidelberg, 1998.
  • [21] Polkowski. L., Skowron, A.: Towards adaptive calculus of granules, Computing with Words in Information/Intelligent Systems (L. A. Zadeh. J. Kacprzyk, Eds.), vol. 1, Physica-Verlag, Heidelberg, 1999. 201-228.
  • [22] Polkowski. L.. Skowron, A.: Rough mereology in information systems. A case study: Qualitative spatial reasoning, Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems (L. Polkowski, S. Tsumoto, T. Y. Lin, Eds.). Physica-Verlag, Heidelberg New York, 2001.
  • [23] Pomykała, J. A.: Approximation operations in approximation space. Bull. Polish Acad. Sci. Math., 35(9-10), 1987. 653-662.
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  • [25] Słowiński. R., Vanderpooten, D.: Similarity Relation as a Basis for Rough Approximations, vol. 53/95 of ICS Research Report. Institute of Computer Science, Warsaw University of Technology, Warsaw, 1995, (see also Advances in Machine Intelligence and Soft Computing (P. P. Wang, Ed.), vol. 4. Duke University Press, 1997, 17-33).
  • [26] Słowiński. R., Vanderpooten, D.: A generalized definition of rough approximations based on similarity, IEEE Transactions on Data and Knowledge Engineering, 12, 2000, 331-336.
  • [27] Stefanowski. J., Tsoukias. A.: Decision rules and valued tolerance, Proc. 2nd Int. Conf on Rough Sets and Current Trends in Computing (RSCTC’2000), Banff, Canada. 2000. October 16-19 (W. Ziarko, Y. Yao. Eds.), Lecture Notes in Artificial Intelligence, 2005. Springer-Verlag, Berlin, 2001, 180-187.
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  • [29] Stepaniuk. J.: Knowledge discovery by application of rough set models. Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems (L. Polkowski. S. Tsumoto, T. Y. Lin, Eds.), Physica-Verlag. Heidelberg New York, 2001, 137-233.
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Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS2-0005-0033
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