@inproceedings{c41a306b004d4c5891182ff2c12d0f30,
title = "Regional spatial analysis combining fuzzy clustering and non-parametric correlation",
abstract = "In this study, regional analysis based on a limited number of data, which is an important real problem in some disciplines such as geosciences and environmental science, was considered for evaluating spatial data. A combination of fuzzy clustering and non-parametrical statistical analysis is made. In this direction, the partitioning performance of a fuzzy clustering on different types of spatial systems was examined. In this way, a regional projection approach has been constructed. The results show that the combination produces reliable results and also presents possibilities for future works.",
author = "B. Tutmez and U. Kaymak",
year = "2013",
doi = "10.1007/978-3-642-33042-1_24",
language = "English",
isbn = "978-3-642-33041-4",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "219--227",
editor = "R. Kruse and M.R. Berthold and C. Moewes and M.A. Gil and P. Grzegorzewski and O. Hryniewicz",
booktitle = "Synergies Of Soft Computing And Statistics For Intelligent Data Analysis",
address = "Germany",
note = "conference; 6th International Conference on Soft Methods in Probability and Statistics; 2012-10-04; 2012-10-06 ; Conference date: 04-10-2012 Through 06-10-2012",
}