Title :
Clustering data with spatial continuity
Author_Institution :
Inst. of Inf. Sci. & Technol., Massey Univ., Palmerston North, New Zealand
fDate :
6/23/1905 12:00:00 AM
Abstract :
Presents an extended version of the fuzzy c-means algorithm that takes into account the probabilistic information of spatial datasets. This spatial probability can be determined by the indicator kriging of geostatistical estimation. The proposed approach is also considered as the fusion of probabilistic and fuzzy evidences, which are complementary to each other in the data clustering process
Keywords :
fuzzy set theory; matrix algebra; pattern clustering; probability; statistical analysis; data clustering; fuzzy c-means algorithm; fuzzy evidence; geostatistical estimation; indicator kriging; probabilistic evidence; probabilistic information; spatial continuity; spatial datasets; spatial probability; Clustering algorithms; Computational Intelligence Society; Equations; Fuzzy sets; Fuzzy systems; Iterative algorithms; Paper technology; Probability; Q measurement; Zinc;
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-7293-X
DOI :
10.1109/FUZZ.2001.1007249
