Abstract
In this study, we present a general overview of Granular Computing being regarded as a coherent conceptual and algorithmic platform supporting the design of intelligent systems. Fundamental formalisms of Granular Computing are identified and discussed. The linkages between Granular Computing and Computational Intelligence are revealed as well.
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References
A.Bargiela, W. Pedrycz, Granular Computing: An Introduction, Kluwer Academic Publishers, Dordercht, 2003.
D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets, Int. J. General Systems 17, 2–3, 1990, 191–209.
E. Hansen, A generalized interval arithmetic, Lecture Notes in Computer Science, Springer Verlag, vol. 29, 1975, 7–18.
L. Jaulin, M. Kieffer, O. Didrit, E. Walter, Applied Interval Analysis, Springer, London, 2001.
A. Korzybski, Science and. Sanity: An Introduction to Non-Aristotelian Systems and General Semantics. 3rd ed. The International Non-Aristotelian Library Publishing Co., Lakeville, C.T., 1933.
T.Y. Lin, Data mining and machine oriented modeling: a granular computing approach, J. of Applied Intelligence, 13, 2, 2000, 113–124.
J. Lukasiewicz, Philosophische Bemerkungen zu mehrwertigen Systemen des Aussagenkalk, C. R. Soc. Sci. Lettres de Varsovie, 23, 1930, 51–77.
J.M. Mendel, On a 50% savings in the computation of the centroid of a symmetrical interval type-2 fuzzy set, Information Sciences, In press, Available online 2 July 2004.
R. Moore, Interval Analysis, Prentice Hall, Englewood Cliffs, NJ, 1966.
S.K. Pal, A. Skowron (eds.), Rough Fuzzy Hybridization. A New trend in Decision-Making, Springer Verlag, Singapore, 1999.
Z. Pawlak, Rough sets, Int. J. Comput. Inform. Sci. 11, 1982, 341–356.
Z. Pawlak, Rough Sets. Theoretical Aspects of Reasoning About Data, Kluwer Academic Publishers, Dordercht, 1991.
W. Pedrycz, Shadowed sets: representing and processing fuzzy sets, IEEE Trans, on Systems, Man, and Cybernetics, part B, 28, 1998, 103–109.
W. Pedrycz (ed.), Granular Computing: An Emerging Paradigm, Physica Verlag, Heidelberg, 2001.
W. Pedrycz, Knowledge-based Clustering, J. Wiley, 2005.
L. Polkowski, A. Skowron (eds.), Rough Sets in Knowledge Discovery, Physica Verlag, Heidelberg, 1998.
A. Skowron, Rough decision problems in information systems, Bulletin de l’Academic Polonaise des Sciences (Tech), 37, 1989, 59–66.
M. Warmus, Calculus of approximations, Bulletin de l’Academie Polonaise des Sciences, 4, 5, 1956, 253–259.
L.A. Zadeh, Fuzzy sets, Information & Control, 8, 1965, 338–353.
L.A. Zadeh, Fuzzy sets and information granularity, In: M.M. Gupta, R.K. Ragade, R.R. Yager, (eds.), Advances in Fuzzy Set Theory and Applications, North Holland, Amsterdam, 1979, 3–18.
L.A. Zadeh, Fuzzy logic = Computing with words, IEEE Trans, on Fuzzy Systems, 4, 1996, 103–111.
L.A. Zadeh, Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic, Fuzzy Sets and Systems, 90, 1997, 111–117.
L.A. Zadeh, From computing with numbers to computing with words-from manipulation of measurements to manipulation of perceptions, IEEE Trans, on Circuits and Systems, 45, 1999, 105–119.
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Pedrycz, W. (2006). Granular Computing: An Overview. In: Abraham, A., de Baets, B., Köppen, M., Nickolay, B. (eds) Applied Soft Computing Technologies: The Challenge of Complexity. Advances in Soft Computing, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31662-0_2
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DOI: https://doi.org/10.1007/3-540-31662-0_2
Publisher Name: Springer, Berlin, Heidelberg
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