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题名: Adaptive ore grade estimation method for the mineral deposit evaluation
作者: Li, Xiao-li1;  Xie, Yu-ling1;  Guo, Qian-jin2;  Li, Li-hong3
关键词: Ore grade estimation ;  Nonlinear and intelligent method ;  Wavelet neural networks
刊名: MATHEMATICAL AND COMPUTER MODELLING
发表日期: 2010-12-01
DOI: 10.1016/j.mcm.2010.04.018
卷: 52, 期:11-12, 页:1947-1956
收录类别: SCI ;  ISTP
文章类型: Article
WOS标题词: Science & Technology ;  Technology ;  Physical Sciences
类目[WOS]: Computer Science, Interdisciplinary Applications ;  Computer Science, Software Engineering ;  Mathematics, Applied
研究领域[WOS]: Computer Science ;  Mathematics
英文摘要: Ore grade estimation is one of the most key and complicated aspects in the evaluation of a mineral deposit. Its complexity originates from scientific uncertainty. This paper introduces a new nonlinear and adaptive method to the problem of ore grade estimation, which is based on the Wavelet Neural Network (WNN) approach, and is designed to receive drill hole information from an orebody and perform ore grade estimation on a block model basis. The nonlinear ore grade estimation method combining the properties of the wavelet transform and the advantages of Artificial Neural Networks (ANNs) provides fast and reliable ore grade estimation, with minimum assumptions and minimum requirements for modeling skills. A number of case studies have been carried out using the new ore grade estimation method. The results obtained and the overall functionality of the method prove that Wavelet Neural Networks can offer a fast and robust grade estimation technique and a valid alternative to well established methodologies in this area. (C) 2010 Elsevier Ltd. All rights reserved.
语种: 英语
WOS记录号: WOS:000281614600006
Citation statistics: 
内容类型: 期刊论文
URI标识: http://cas-ir.dicp.ac.cn/handle/321008/141811
Appears in Collections:中国科学院大连化学物理研究所_期刊论文

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作者单位: 1.Univ Sci & Technol Beijing, Sch Civil & Environm Engn, Beijing 100083, Peoples R China
2.Chinese Acad Sci, State Key Lab Mol React Dynam, Inst Chem, Beijing 100190, Peoples R China
3.Henan Univ Sci & Technol, Coll Vehicle & Mot Power Engn, Luoyang, Peoples R China

Recommended Citation:
Li, Xiao-li,Xie, Yu-ling,Guo, Qian-jin,et al. Adaptive ore grade estimation method for the mineral deposit evaluation[J]. MATHEMATICAL AND COMPUTER MODELLING,2010,52(11-12):1947-1956.
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