Multi-Attribute Technological Modeling of Coal Deposits Based on the Fuzzy TOPSIS and C-Mean Clustering Algorithms

Energies

Jasmina Nedeljković Ostojić¹  Zoran Gligorić²  Miloš Gligorić²  Čedomir Beljić²  Slavko Torbica²  Svetlana Štrbac Savić³ 

[1] Department of Geodesy, Belgrade University College of Applied Studies in Civil Engineering and Geodesy, Hajduk Stanka 2, 11000 Belgrade, Serbia;Faculty of Mining and Geology, University of Belgrade, Đušina 7, 11000 Belgrade, Serbia;The School of Electrical and Computer Engineering of Applied Studies, Vojvode Stepe 283, 11000 Belgrade, Serbia;

关键词: coal deposit;    block model;    technological model;    fuzzy TOPSIS;    fuzzy C-mean clustering;    Fukuyama-Sugeno validity functional;    adjusted Rand index;    entropy;   

DOI  :  10.3390/en9121059

来源: DOAJ

【 摘 要 】

The main aim of a coal deposit model is to provide an effective basis for mine production planning. The most applied approach is related to block modeling as a reasonable global representation of the coal deposit. By selection of adequate block size, deposits can be well represented. A block has a location in XYZ space and is characterized by adequate attributes obtained from drill holes data. From a technological point of view, i.e., a thermal power plant’s requirements, heating value, sulfur and ash content are the most important attributes of coal. Distribution of attributes’ values within a coal deposit can vary significantly over space and within each block as well. To decrease the uncertainty of attributes’ values within blocks the concept of fuzzy triangular numbers is applied. Production planning in such an environment is a very hard task, especially in the presence of requirements. Such requirements are considered as target values while the values of block attributes are the actual values. To make production planning easier we have developed a coal deposit model based on clustering the relative closeness of actual values to the target values. The relative closeness is obtained by the TOPSIS method while technological clusters are formed by fuzzy C-mean clustering. Coal deposits are thus represented by multi-attribute technological mining cuts.

【 授权许可】

Unknown