| 利用人工神经网络自动识别煤田测井岩性 |
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| 引用本文： | 董守华,陈辉.利用人工神经网络自动识别煤田测井岩性[J].中国煤田地质,1996,8(1):66-70. |
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| 作者姓名： | 董守华 陈辉 |
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| 作者单位： | 中国矿业大学，中国科技大学 |
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| 摘 要： | 介绍采用人工神经网络（ＡＮＮ）模型，借助于误差逆转播算法，应用到煤田测井岩性自动识别中，效果较好。为提高该方法的实用性，通过对误差逆传播算法的改进，并经过验算，表明了其优越性；文中采用多层人工神经ＢＰ网络模型，对较大样本（４８组）进行学习，可以识别８种岩性，说明了该方法的实用性。
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| 关 键 词： | 人工神经网络，误差逆传播算法，岩性自动识别，煤田测井 |
LITHOLOGY AUTOMATIOC IDENTIFICATION FOR WELL -LOGGING DATA FROM COAL MINE USING ARTIFICIAL NERVOUS NETWORK(ANN) |
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| Dong Shouhua.LITHOLOGY AUTOMATIOC IDENTIFICATION FOR WELL -LOGGING DATA FROM COAL MINE USING ARTIFICIAL NERVOUS NETWORK(ANN)[J].Coal Geology of China,1996,8(1):66-70. |
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| Authors: | Dong Shouhua |
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| Institution: | Dong Shouhua(China University of Minning and Technology)Chen Hui (University of Science and Technology of China) |
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| Abstract: | In this paper Bp-Networks of ANN are used in Zone of Lithology automatic i-dentification foe logging data from coal mines. The algorithm, Error Back-propagation wasimproved ,its using was raised.The calculation to synthetic data and real data indicates that itis easy to do,and has high accuracy,adaptation,fault-tolerarce etc.compared with statistical method and crossplotting method. |
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| Keywords: | rtificial nervous network errorback-propagation algorithm lithology auto-matic identification |
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