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Tytuł artykułu

From Numeric to Granular Description and Interpretation of Information Granules

Autorzy
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Fuzzy sets (membership functions) are numeric constructs. In spite of the underlying semantics of fuzzy sets (which is inherently linked with the higher level of abstraction), the membership grades and processing of fuzzy sets themselves emphasize the numeric facets of all pursuits stressing the numeric nature of membership grades and in this way reducing the interpretability and transparency of results. In this study, we advocate an idea of a granular description of membership functions where instead of numeric membership grades, introduced are more interpretable granular descriptors (say, low, high membership, etc.). Granular descriptors are formalized with the aid of various formal schemes available in Granular Computing, especially sets (intervals), fuzzy sets, and shadowed sets. We formulate a problem of a design of granular descriptors as a certain optimization task, elaborate on the solutions and highlight some areas of applications.
Wydawca
Rocznik
Strony
399--412
Opis fizyczny
Bibliogr. 15 poz., wykr.
Twórcy
autor
  • Department of Electrical & Computer Engineering, University of Alberta, Edmonton, Canada
Bibliografia
  • [1] I. García-Honrado, E. Trillas, An essay on the linguistic roots of fuzzy sets, Information Sciences, 181(19), 2011, 4061-4074.
  • [2] B. Kuipers, Qualitative Reasoning, MIT Press, 1994.
  • [3] J. Mira, Symbols versus connections: 50 years of artificial intelligence, Neurocomputing, 71(4-6), 2008, 671-680.
  • [4] R. Moore, R. B. Kearfott, M.J. Cloud, Introduction to Interval Analysis, SIAM, Philadelphia, 2009.
  • [5] Z. Pawlak, Rough sets, International Journal of Information and Computer Science, 11(15), 1982, 341-356.
  • [6] Z. Pawlak, A. Skowron, Rudiments of rough sets, Information Sciences, 177(1), 2007, 3-27.
  • [7] Z. Pawlak, A. Skowron, Rough sets and Boolean reasoning, Information Sciences, 177(1), 2007, 41-73.
  • [8] A. Pedrycz, K. Hirota, W. Pedrycz, F. Dong, Granular representation and granular computing with fuzzy sets, Fuzzy Sets and Systems, 203, 2012, 17-32.
  • [9] W. Pedrycz, Shadowed sets: representing and processing fuzzy sets, IEEE Trans. on Systems, Man, and Cybernetics, part B, 28, 1998, 103-109.
  • [10] W. Pedrycz, Statistically grounded logic operators in fuzzy sets, European Journal of Operational Research, 193(2), 2009, 520-529.
  • [11] W. Pedrycz, From fuzzy sets to shadowed sets: interpretation and computing, International Journal of Intelligent Systems, 24(1), 2009, 48-61.
  • [12] S.C. Shapiro (ed.), Encyclopedia of Artificial Intelligence, volumess 1 & 2, 2nd edition, John Wiley and Sons, New York, 1990.
  • [13] F. van den Bergh, A.P. Engelbrecht, A study of particle swarm optimization particle trajectories, Information Sciences, 176(8), 2006, 937-971.
  • [14] L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning, Information Sciences, 8, 1975, 199-249.
  • [15] L. A. Zadeh, A note on Z-numbers, Information Sciences, 181, 2011, 2923-2932.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ec5a7f25-d5ad-4454-8c28-b0bb1b16a01e
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