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For applications of data mining techniques in geosciences, through mining spatial databases which are constructed with geophysical and geochemical data measured in fields, the knowledge, such as the spatial distribution of geological targets, the geophysical and geochemical characteristics of geological targets, the differentiation among the geological targets, and the relationship among geophysical...
For applications of clustering algorithms, the key techniques are to handle complicatedly distributed clusters and process massive data effectively and efficiently. On the basis of analysis and research of traditional clustering algorithms, a clustering algorithm based on density and adaptive density-reachable is presented in this paper, which can handle clusters of arbitrary shapes, sizes and densities...
This paper analyses the advantages and disadvantages of the K-means algorithm and the DENCLUE algorithm. In order to realise the automation of clustering analysis and eliminate human factors, both partitioning and density-based methods were adopted, resulting in a new algorithm - Clustering Algorithm based on object Density and Direction (CADD). This paper discusses the theory and algorithm design...
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