Abstract
Abstract
Visualization of multidimensional data is a new way of statistical analysis of so-called statistical graphical methods. These methods allow to classify some analyzed objects, including their various features. Facing grained materials problems, like coal or ores many characteristics have an influence on the quality of product. In case of coal, many features must be taken into consideration to determine quality of the material. Apart from most obvious characteristics like particle size, particle density or ash contents there are many others which cause significant differences between considered types of material. In the paper the application of Multidimensional Scaling Method is presented which is one of the multidimensional data visualization techniques. To this purpose, sampling of three types of coal was performed, which were 31, 34.2 and 35 (according to Polish classification of coal types). First, the material was screened on sieves and then divided into density fractions. Next step was to analyze chemically the obtained particle and size fractions of researched coal. Then, the Multidimensional Scaling Method was applied to visualize the investigated set of data. It was proved 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 Multidimensional Scaling Method is new technique of data analysis concerning widely understood mineral processing.
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16 articles.
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