| 锡矿山硅化灰岩识别的人工神经网络模型 |
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| 引用本文： | 卢新卫,胡明星.锡矿山硅化灰岩识别的人工神经网络模型[J].地质与勘探,1999,35(6):52-54. |
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| 作者姓名： | 卢新卫 胡明星 |
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| 作者单位： | 1. 南京大学·南京·210093
2. 中国矿业大学·徐州·221008 |
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| 摘 要： | 硅化／硅化岩石是锡矿山锑矿的一种很有效的找矿标志。因此，如何正确地识别硅化岩石与原岩，以及硅化的强弱对于找矿有着重要意义。将人工神经网络模型引入锡矿硅化灰岩识别的研究中，识别成功率达到９３．３％。结果表明，该方法简便实用，性能良好，可望成为岩石，矿物识别的一种有效的辅助手段。
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| 关 键 词： | 硅化灰岩识别 人工神经网络 BP训练算法 锡矿山 |
| 修稿时间： | 1998-03-00 |
ARTIFICIAL NEURAL NETWORK MODEL OF XIKUANGSHAN SILICIFIED LIMESTONE RECOGNITION |
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| Lu Xinwei,Hu Mingxing.ARTIFICIAL NEURAL NETWORK MODEL OF XIKUANGSHAN SILICIFIED LIMESTONE RECOGNITION[J].Geology and Prospecting,1999,35(6):52-54. |
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| Authors: | Lu Xinwei Hu Mingxing |
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| Abstract: | Silicify or silicified rock is one more efficacious sign for exploring mine in Xikuangshan antimony deposit.So it has more important significance that how to recognize silicified rock from host rock and the extent of silicify.The paper firstly applied artificial neural network to recognize the pattern of silicified limestone, with the rate of success reaching 93.3%. The results show that artificial neural network approach is objective, quite satisfactory and tendency might serve as an effective technique for recognition of rocks and minerals. |
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| Keywords: | silicified limestones artificial neural network back propagation algorithm Xikuangshan |
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