APPLICATION OF RELEVANCE MAPS IN MULTIDIMENSIONAL CLASSIFICATION OF COAL TYPES

作者：Niedoba Tomasz^*

来源：Archives of Mining Sciences, 2015, 60(1): 93-106.

DOI：10.1515/amsc-2015-0007

• relevance maps
• multidimensional data visualization
• coal
• identification of data
• pattern recognition

Multidimensional data visualization methods are a modern tool allowing to classify some analyzed objects. In the case of grained materials e.g. coal, many characteristics have an influence on the material quality. In case of coal, apart from most obvious features like particle size, particle density or ash contents there are many others which cause significant differences between considered types of material. The paper presents the possibility of applying visualization techniques for coal type identification and determination of significant differences between various types of coal. Author decided to apply relevance maps to achieve this purpose. Three types of coal -31, 34.2 and 35 (according to Polish classification of coal types) were investigated, which were initially screened on sieves and then divided into density fractions. Then, each size-density fraction was chemically analyzed to obtain other characteristics. It was stated that the applied methodology allows to identify certain coal types efficiently and can be used as a qualitative criterion for grained materials. However, it was impossible to achieve such identification comparing all three types of coal together. The presented methodology is new way of analyzing data concerning widely understood mineral processing.

• 出版日期2015-3