Application of tetrahedral mesh model based on neural network in solid mineral reserve estimation

Junfang Gong; Xincai Wu; Xiuguo Liu; Shengwen Li

1st International ICST Workshop on Knowledge Discovery and Data Mining

Research Article

Application of tetrahedral mesh model based on neural network in solid mineral reserve estimation

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/wkdd.2008.2692,
    author={Junfang Gong and Xincai Wu and Xiuguo Liu and Shengwen Li},
    title={Application of tetrahedral mesh model based on neural network in solid mineral reserve estimation},
    proceedings={1st International ICST Workshop on Knowledge Discovery and Data Mining},
    publisher={ACM},
    proceedings_a={WKDD},
    year={2010},
    month={5},
    keywords={},
    doi={10.4108/wkdd.2008.2692}
}

Junfang Gong
Xincai Wu
Xiuguo Liu
Shengwen Li
Year: 2010
Application of tetrahedral mesh model based on neural network in solid mineral reserve estimation
WKDD
ACM
DOI: 10.4108/wkdd.2008.2692

Junfang Gong¹^,*, Xincai Wu¹, Xiuguo Liu¹, Shengwen Li¹

1: Department of Information Engineering, China University of Geosciences, WuHan

*Contact email: gjf4000@163.com

Abstract

Mineral reserve estimation involves large amounts of geological data, and the traditional manual computation method is a heavy and fussy work. Computing mineral reserve with 3D orebody modeling can increase the efficiency heavily of reserve estimation and management. On the basis of analyzing several 3D orebody modeling methods, this paper choose tetrahedral mesh model to construct orebody, and introduces a mineral reserve estimation method based on neural network. The main advantages of this technique are an according management for orebody boundary and inner grade distribution, as well as its precision. Therefore, this technique has an academic and practical value.

Published: 2010-05-16
Publisher: ACM
Modified: 2010-05-16

: http://dx.doi.org/10.4108/wkdd.2008.2692