Fuzzy Approach to Ecological Data Analysis
نویسنده
چکیده
The paper focuses on the fuzzy extensions of two data analysis methods, namely the fuzzy cluster analysis and the fuzzy interpolation of spatial data (the so-called fuzzy kriging) and their suitability for ecological applications. Both extensions utilize exact (crisp) measurement data as well as imprecise data defined as fuzzy numbers or fuzzy vectors. Fuzzy clustering of fuzzy data (conical fuzzy vectors) and fuzzy kriging methods are useful tools with a potential of utilizing vast pieces of information available as inexact or uncertain data. We have to deal with such data in many ecological applications. The paper presents an example of the analysis of ecological data and two fuzzy data analysis systems developed at the University of Kiel. Key-Words: fuzzy clustering, conical fuzzy vector, fuzzy classification, fuzzy kriging, fuzzy regionalization, ecological application 1 Uncertainty and Heterogeneity of
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