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Journal of Central South University

, Volume 25, Issue 2, pp 342–356 | Cite as

Quadratic investigation of geochemical distribution by backward elimination approach at Glojeh epithermal Au(Ag)-polymetallic mineralization, NW Iran

Article

Abstract

The correspondence analysis will describe elemental association accompanying an indicator samples. This analysis indicates strong mineralization of Ag, As, Pb, Te, Mo, Au, Zn and to a lesser extent S, W, Cu at Glojeh polymetallic mineralization, NW Iran. This work proposes a backward elimination approach (BEA) that quantitatively predicts the Au concentration from main effects (X), quadratic terms (X2) and the first order interaction (X i ×X j ) of Ag, Cu, Pb, and Zn by initialization, order reduction and validation of model. BEA is done based on the quadratic model (QM), and it was eliminated to reduced quadratic model (RQM) by removing insignificant predictors. During the QM optimization process, overall convergence trend of R2, R2(adj) and R2(pred) is obvious, corresponding to increase in the R2(pred) and decrease of R2. The RQM consisted of (threshold value, Cu, Ag×Cu, Pb×Zn, and Ag2–Pb2) and (Pb, Ag×Cu, Ag×Pb, Cu×Zn, Pb×Zn, and Ag2) as main predictors of optimized model according to 288 and 679 litho-samples in trenches and boreholes, respectively. Due to the strong genetic effects with Au mineralization, Pb, Ag2, and Ag×Pb are important predictors in boreholes RQM, while the threshold value is known as an important predictor in the trenches model. The RQMs R2(pred) equal 74.90% and 60.62% which are verified by R2 equal to 73.9% and 60.9% in the trenches and boreholes validation group, respectively.

Key words

correspondence analysis first order interaction reduced quadratic model (RQM) optimized model order reduction and validation strong genetic effects 

后向消元法对伊朗西北地区 Glojeh 超热 Au(Ag)-多金属矿地球化学元素分布的二次元分析

摘要

本研究对指示样品中的元素组合进行描述。 结果表明: 在伊朗西北地区 Glojeh 多金属矿中, Ag, As, Pb, Te, Mo, Au 和 Zn 发生强烈矿化, 而 S, W 和 Cu 矿化程度较低。 本文采用后向消元法通过初始化, 降阶和模型验证对 Au 浓度的主效应 (X) 和二次项 (X2) 以及 Ag, Cu, Pb 和 Zn 的一阶交互作用(X i ×X j ) 进行定量预测。 后向消元法是基于二次多项式模型完成的, 通过去除不重要的指示变量进行消元而得到简化二次多项式模型。 在二次多项式优化过程中, R2(pred)增加而 R2 减小, R2, R2(adj) 和R2(pred)都具有明显的收敛趋势。 基于 288 个沟槽和 679 个钻孔岩石样品的预测结果表明: 简化二 次多项式模型包含阈值变量(Cu, Ag×Cu, Pb×Zn 和 Ag 2–Pb2) 和主指示变量 (Pb, Ag×Cu, Cu×Zn, Pb×Zn 和 Ag2)。 由于 Au 矿化具有强烈的遗传效应, Pb, Ag2 和 Ag×Pb 为沟槽样品简化二次多项式模型的重要指示变量, 而阈值变量为钻孔样品模型的重要指示变量。验证组沟槽样品和钻孔样品简化二次多项式模型的R2(pred)分别为74.9%和 60.62%, R2 分别为 73.9%和 60.9%。

关键词

相关性分析 一阶交互作用 简化二次多项式模型 优化模型 降阶和验证 强烈遗传效应 

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Notes

Acknowledgements

We would also like to thank Mr. Fattahi and Mr. Hemmati for their help in organizing this data. Finally, and more formally, we would like to acknowledge the support of the IMIDRO (Iranian Mines and Mining Industries Development & Renovation Organization) for our research.

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© Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mining and Metallurgical EngineeringAmirkabir University of TechnologyTehranIran

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