| 人工神经网络在澜沧江某电站坝基右岸复杂岩体分类中的应用 |
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| 引用本文： | 赵红亮,陈剑平.人工神经网络在澜沧江某电站坝基右岸复杂岩体分类中的应用[J].煤田地质与勘探,2003,31(1):31-33. |
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| 作者姓名： | 赵红亮 陈剑平 |
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| 作者单位： | 吉林大学建设工程学院, 吉林 长春 130026 |
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| 基金项目： | 教育部资助优秀年轻教师基金项目(No.120413133)，教育部留学回国人员科研启动基金(No.20011302008) |
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| 摘 要： | 结合云南省澜沧江某水电站工程实例,应用BP人工神经网络方法建立3层BP网络模型。选取岩石单轴抗压强度、岩体完整性系数、RQD、节理面粗糙度系数、节理面风化变并系数、透水性系数等6个影响因素为输入变量,对坝基右岸复杂岩体进行质量分类。通过对比分析发现,BP网络模型经多次学习后,预测岩体质量类别时辩识能力较强,结果可靠,取得了较好的实际应用效果。
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| 关 键 词： | 人工神经网络 岩体质量 分类 |
| 文章编号： | 1001-1986(2003)01-0031-03 |
| 收稿时间： | 2002-08-07 |
| 修稿时间： | 2002年8月7日 |
The application of artificial neural network in complicated rockmass quality classification of a hydraulic power station on the right bank of Lancang River |
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| ZHAO Hong-Hang,CHEN Jian-ping.The application of artificial neural network in complicated rockmass quality classification of a hydraulic power station on the right bank of Lancang River[J].Coal Geology & Exploration,2003,31(1):31-33. |
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| Authors: | ZHAO Hong-Hang CHEN Jian-ping |
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| Institution: | Jilin University, Changchun 130026, China |
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| Abstract: | The paper applies the method of the back propagation artificial neural network on a hydraulic power station on the Lancang River, Yunnan Province,choosing six influential factors on the rock mass quality as the input variables,such as one axis compressive strength of rock, sound degree coefficient of rock mass, rock quality designation, roughness degree coefficient of joint surface, alteration coefficient of joint surface, permeability coefficient,and classifies the complicated rock mass on the right bank of the dam foundation. Through comparison analysis, the result of predicting the rock mass is exact and credible after the model of the back propagation artificial neural network learning enough times.The application has gained a good effect. |
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| Keywords: | artificial neural network rockmass quality classification |
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