Regional spatial analysis combining fuzzy clustering and non-parametric correlation

Autor:	Tutmez, Bulent, Uzay Kaymak, Kruse, R., Berthold, MR, Moewes, C., Gil, Ma, Grzegorzewski, P., Hryniewicz, O.
Přispěvatelé:	Information Systems IE&IS
Jazyk:	angličtina
Rok vydání:	2013
Předmět:	Fuzzy clustering business.industry Correlation clustering Nonparametric statistics FLAME clustering Pattern recognition Artificial intelligence business Projection (set theory) Cluster analysis Spatial analysis Rank correlation
Zdroj:	ResearcherID Synergies of Soft Computing and Statistics for Intelligent Data Analysis ISBN: 9783642330414 SMPS Synergies Of Soft Computing And Statistics For Intelligent Data Analysis, 219-227 STARTPAGE=219;ENDPAGE=227;TITLE=Synergies Of Soft Computing And Statistics For Intelligent Data Analysis
DOI:	10.1007/978-3-642-33042-1_24
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e8c9129b9f50fef85bad9ef58504078 https://doi.org/10.1007/978-3-642-33042-1_24 Zobrazit plný text záznamu