Abstract | ||
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In Geoinformation systems (GIS) there is need to model spatial region with indeterminate boundary and under uncertainties. Although fuzzy logic methods are of great interest in many GIS applications, however the traditional fuzzy logic has two important deficiencies: first, to apply the fuzzy logic, we need to assign, to every property and for every value, a crisp membership function and second, it does not distinguish between the situation in which there is no knowledge about a certain statement and a situation that the belief to the statement in favor and against is the same. In order to solve these problems, we motivate to use intuitionistic fuzzy logic. This paper gives fundamental concepts and properties of an intuitionistic fuzzy spatial region. We provide a theoretical framework for both dominant ontologies used in GIS; namely point-set topology and Region Connected calculus. |
Year | DOI | Venue |
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2004 | 10.1007/978-3-540-25929-9_51 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
fuzzy logic,object model,topological space,membership function | Defuzzification,Fuzzy classification,Fuzzy set operations,Computer science,Fuzzy logic,Fuzzy mathematics,Fuzzy set,Artificial intelligence,Fuzzy number,Type-2 fuzzy sets and systems | Conference |
Volume | ISSN | Citations |
3066 | 0302-9743 | 4 |
PageRank | References | Authors |
0.46 | 6 | 1 |
Name | Order | Citations | PageRank |
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Mohammad Reza Malek | 1 | 30 | 7.30 |