A fuzzy sets theoretic approach to approximate spatial reasoning

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dc.contributor.author Li, Sanjiang en_US
dc.contributor.author Li, Yongming en_US
dc.contributor.editor en_US
dc.date.accessioned 2010-05-28T09:47:09Z
dc.date.available 2010-05-28T09:47:09Z
dc.date.issued 2004 en_US
dc.identifier 2007004958 en_US
dc.identifier.citation Li Sanjiang and Li Yongming 2004, 'A fuzzy sets theoretic approach to approximate spatial reasoning', IEEE Computational Intelligence Society, vol. 12, no. 6, pp. 745-754. en_US
dc.identifier.issn 1063-6706 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/9051
dc.description.abstract Relational composition-based reasoning has become the most prevalent method for qualitative reasoning since Allen's 1983 work on temporal intervals. Underlying this reasoning technique is the concept of a jointly exhaustive and pairwise disjoint set of relations. Systems of relations such as RCC5 and RCC8 were originally developed for ideal regions, not subject to imperfections such as vagueness or fuzziness which are found in many applications in geographic analysis and image understanding. This paper, however, presents a general method for classifying binary topological relations involving fuzzy regions using the RCC5 or the RCC8 theory. Our approach is based on fuzzy set theory and the theory of consonant random set. Some complete classifications of topological relations between fuzzy regions are also given. Furthermore, two composition operators on spatial relations between fuzzy regions are introduced in this paper. These composition operators provide reasonable relational composition-based reasoning engine for spatial reasoning involving fuzzy regions. en_US
dc.language en_US
dc.publisher IEEE Computational Intelligence Society en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/TFUZZ.2004.836100 en_US
dc.title A fuzzy sets theoretic approach to approximate spatial reasoning en_US
dc.parent IEEE Transactions on Fuzzy Systems en_US
dc.journal.volume 12 en_US
dc.journal.number 6 en_US
dc.publocation USA en_US
dc.identifier.startpage 745 en_US
dc.identifier.endpage 754 en_US
dc.cauo.name FEIT.School of Systems, Management and Leadership en_US
dc.conference Verified OK en_US
dc.for 080100 en_US
dc.personcode 106033 en_US
dc.personcode 0000046414 en_US
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Consonant random set , fuzzy logic, fuzzy region mode, region connection calculus, relational composition, spatial relation en_US
dc.staffid en_US


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