Assessment of coal deposit using multivariate statistical analysis techniques
Energy Sources, Part A: Recovery, Utilization and Environmental Effects, vol.38, no.7, pp.1002-1006, 2016 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 38 Issue: 7
- Publication Date: 2016
- Doi Number: 10.1080/15567036.2010.540635
- Journal Name: Energy Sources, Part A: Recovery, Utilization and Environmental Effects
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.1002-1006
- Keywords: Calorific value, cluster analysis, coal, discriminant analysis, multivariate statistical analysis techniques, Turkey
- Bilecik Şeyh Edebali University Affiliated: Yes
Abstract
© 2016 Taylor & Francis Group, LLC.Energy is one of the indispensable factors regarding the economic development of Turkey. Examination of calorific values in coal deposits has importance in the production of energy, and thus planning of the coal deposit. In this article, multivariate statistical analysis techniques, including cluster analysis and discriminant analysis, were applied to calorific values obtained from boreholes. Cluster analysis grouped borehole locations into two clusters based on the similarity of calorific values. Afterwards, discriminant functions were supported to cluster analysis and developed a linear discriminant function. Based on the locations of the boreholes, it was concluded that calorific values are a highly central part of the coal deposit. Thus, this article shows the usefulness of multivariate statistical analysis techniques for understanding spatial variation of coal deposits and effective deposit management.