基于小波神经网络(WNN)和浓度-体积(C-V)分形方法的伊朗东部Shahr-e-Babak地区斑岩铜矿变质带圈定

IF 1.1 Q3 MINING & MINERAL PROCESSING
B. S. Saljoughi, A. Hezarkhani
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引用次数: 0

摘要

在本文中,我们旨在实现两个具体目标。首先,研究了基于小波理论与人工神经网络相结合的小波神经网络技术在矿石品位估计中的适用性。利用不同的小波作为激活函数,对伊朗东南部Shahr-e-Babak地区斑岩矿床下生带的钻孔资料进行了Cu品位估算。WNN的扩张、平移等参数是固定的,在学习过程中只对网络的权值进行优化。这种网络在函数学习和估计方面的有效性与普通克里格(OK)进行了比较。其次,基于小波神经网络(WNN)和OK方法的估计,利用浓度-体积(C-V)分形模型,圈定了铜斑岩矿床下生带的钾质蚀变区和植物蚀变区;为此,首先基于OK和WNN的结果生成C-V对数对数图。然后利用这些图确定蚀变带的Cu阈值。为了研究地质模型与C-V分形结果的相关性,应用对数比矩阵。结果表明,小波神经网络的Cu值小于1.1%,总体精度(OA)为0.74,与叶状蚀变带有较多的重叠体素。三维地质建模得到的钾蚀变带与C-V分形模型的高富集带的空间相关性表明,蚀变带的Cu值在1.1% ~ 2.2%之间,OA为0.72,最终与Cu值存在适当重叠,大于2.2%,OA为0.7。总体而言,研究结果表明,OA大于OK的Morlet激活函数(WNN)可以取代定性方法,成为一种适合的、鲁棒的蚀变带定量建模工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Delineation of Alteration Zones Based on Wavelet Neural Network (WNN) and Concentration–Volume (C-V) Fractal Methods in the Hypogene Zone of Porphyry Copper Deposit, Shahr-e-Babak District, SE Iran
In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of wavelet neural network (WNN) technique in ore grade estimation, which is based on integration between wavelet theory and Artificial Neural Network (ANN). Different wavelets are applied as activation functions to estimate Cu grade of borehole data in the hypogene zone of porphyry ore deposit, Shahr-e-Babak district, SE Iran. WNN parameters such as dilation and translation are fixed and only the weights of the network are optimized during its learning process. The efficacy of this type of network in function learning and estimation is compared with Ordinary Kriging (OK). Secondly, we aim to delineate the potassic and phyllic alteration regions in the hypogene zone of Cu porphyry deposit based on the estimation obtained of WNN and OK methods, and utilize Concentration–Volume (C–V) fractal model. In this regard, at first C–V log–log plots are generated based on the results of OK and WNN. The plots then are used to determine the Cu threshold values of the alteration zones. To investigate the correlation between geological model and C-V fractal results, the log ratio matrix is applied. The results showed that, Cu values less than 1.1% from WNN have more overlapped voxels with phyllic alteration zone by overall accuracy (OA) of 0.74. Spatial correlation between the potassic alteration zones resulted from 3D geological modeling and high concentration zones in C-V fractal model showed that the alteration zone has Cu values between 1.1% and 2.2% with OA of 0.72 and finally have an appropriate overlap with Cu values greater than 2.2% with OA of 0.7. Generally, the results showed that the WNN (Morlet activation function) with OA greater than OK can be can be a suitable and robust tool for quantitative modeling of alteration zones, instead of qualitative methods.
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来源期刊
Journal of Mining and Environment
Journal of Mining and Environment MINING & MINERAL PROCESSING-
CiteScore
1.90
自引率
25.00%
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