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Fuzzy clustering in geospatial analysis

机译:地理空间分析中的模糊聚类

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摘要

The aim of this work is to explore the method of fuzzy clustering applied for classification of spatial objects or generic geospatial analysis and cluster analysis as a classification of objects by mutual similarities and organize data into groups. Clustering techniques fall into unsupervised methods, meaning that they do not use predefined class identifiers. The biggest potential of clustering is in recognizing the basic data structures, not only for classification and identification of samples, but also the reduction of models and optimization.
机译:这项工作的目的是探索用于空间对象分类或通用地理空间分析和聚类分析的模糊聚类方法,以通过相互相似性将对象分类,并将数据组织成组。聚类技术属于无监督方法,这意味着它们不使用预定义的类标识符。聚类的最大潜力在于识别基本数据结构,不仅用于样本的分类和识别,还包括模型的简化和优化。

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