Lithological classification of cement quarry using discriminant algorithms
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Date
2019
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Journal Of Central South Univ
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
As such in any industrial raw material site characterization study, making a lithological evaluation for cement raw materials includes a description of physical characteristics as well as grain size and chemical composition. For providing the cement components in accordance with the specifications required, making the classification of the cement raw material pit is needed. To make this identification in a spatial system at a quarry stage, the supervised pattern recognition analysis has been performed. By using four discriminant analysis algorithms, lithological classifications at three levels, which are with limestone, marly-limestone (calcareous marl) and marl, have been made based on the main chemical components such as calcium oxide (CaO), alumina (Al2O3), silica (SiO2), and iron (Fe2O3). The results show that discriminant algorithms can be used as strong classifiers in cement quarry identification. It has also recorded that the conditional and mixed classifiers perform better than the conventional discriminant algorithms.
Description
Keywords
cement, discriminant analysis, lithology classification, quarry identification
Journal or Series
Journal of Central South University
WoS Q Value
Q3
Scopus Q Value
Q1
Volume
26
Issue
3
