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Bitmap based structures for the modeling of fuzzy entities

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Bitmap models are a known technique to model field based geographic information. Commonly, geographic information is modelled in a crisp sense, even though in reality it most likely is an approximation. In this article, we present the use of bitmap based structures to model imprecise or uncertain locations and ditto regions: these structures should be considered to be extensions of respectively a point and a polygon. The imprecission or uncertainty is modelled using fuzzy set theory. Apart from presenting the structures, appropriate operators are denned and explained.
Rocznik
Strony
147--164
Opis fizyczny
Bibliogr. 19 poz., rys., wykr.
Twórcy
autor
autor
  • Department of Telecommunications and Information Processing, Ghent University, Sint Pietersnieuwstraat 41, 9000 Ghent, Belgium, jorg.verstraete@tehn.ugent.be
Bibliografia
  • ANGEL, E.S. (2003) Interactive Computer Graphics: A Top-Down Approach with OpenGL. Addison-Wesley.
  • BEAUBOUEF, T. and PETRY, F.(2001) Vagueness in Spatial Data: Rough Set and Egg-Yolk Approaches. Proc. IEA/AIE 2001 Conf., Budapest, Hungary, 2001. Eng. of Intelligent Systems: Lecture Notes in AI 2070. Springer-Verlag, 367-373.
  • CLEMENTINI, E. (2004) Modeling Spatial Objects Affected by Uncertainty. In: R. De Caluwe, De Ire G., Bordogna G., eds., Spatio- Temporal Databases - Flexible Querying and Reasoning. Springer-Verlag, 211-236.
  • COHN, A.G. and GOTTS, N.M.. (1994) Spatial regions with undetermined boundaries. Proceedings of the Second ACM Workshop on Advances in Geographic Information Systems, 52-59.
  • DUBOIS, D. and PRADE, H. (1997) The three semantics of fuzzy sets. Fuzzy Sets and Systems 90, 141-150.
  • DUBOIS, D. and PRADE, H. (2000) Fundamentals of Fuzzy Sets. Kluwer Academic Publishers.
  • DUBOIS, D. and PRADE, H. (2001) Possibility theory, probability theory and multiple-valued logics: A clarification. Annals of Mathematics and Artificial Intelligence 32, 35-66.
  • FOLEY, VAN DAM, FEINER, H. (1996) Computer Graphics. Addison-Wesley.
  • GOTTS, N.M. and COHN, A.G. (1995) A mereological approach to representing spatial vagueness. Working Papers, Ninth International Workshop on Qualitative Reasoning, 246-255.
  • HALLEZ, A., VERSTRAETE, J., DE TRÉ, G. and DE CALUWE, R. (2002) Contourline Based Modelling of Vague Regions. Proceedings of the 9th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU 2002, July 1-5, Annecy, France. EISA, Universite de Savoie, 1721-1726.
  • KLIR, G.J. and YUAN; B. (1995) Fuzzy Sets and Fuzzy Logic: Theory and applications. Prentice Hall, New Jersey.
  • MORRIS, A. (2001) Why Spatial Databases Need Fuzziness. Proceedings of IFSA/NAFIPS 2001, Vancouver, Canada (CD), 2446-2451.
  • PRADE, H. (1982) Possibility sets, fuzzy sets and their relation to Lukasiewicz logic. Proc. 12th Int. Symp. on Multiple-Valued Logic, 223-227.
  • RIGAUX, P., SCHOLL, M. and VOISARD, A. (2002) Spatial Databases with Applications to GIS. Morgan Kaufman Publishers.
  • SHEKHAR, S. and CHAWLA, S. (2003) Spatial Databases: A Tour. Pearson Education Inc.
  • SOMODEVILLA, M.J. and PETRY, F.E. (2004) Fuzzy Minimum Bounding Rectangles, In: R. De Caluwe, G. De Tre, G. Bordogna, eds., Spatio- Temporal Databases - Flexible Querying and Reasoning. Springer-Verlag, 237-263.
  • VERSTRAETE, J., DE TRÉ, G., DE CALUWE, R. and HALLEZ, A. (2005) Field Based Methods for the Modeling of Fuzzy Spatial Data. In: F. Petry, V. Robinson, M. Cobb, eds., Fuzzy Modeling with Spatial Information for Geographic Problems. Springer-Verlag, 41-69.
  • ZADEH, L. (1975) The concept of a linguistic variable and its application to approximate reasoning I, II, III. Information Sciences 8, 199-251, 301-357, 9, 43-80.
  • ZIMMERMAN, H.J. (1999) Practical Applications of Fuzzy Technologies. Kluwer Academic Publishers.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0010-0057
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