| 金矿围岩稳定性分类指标的确定方法研究 |
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| 引用本文： | 王学知,赵春风,王连国. 金矿围岩稳定性分类指标的确定方法研究[J]. 地下空间与工程学报, 2007, 3(6): 1051-1053,1068 |
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| 作者姓名： | 王学知 赵春风 王连国 |
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| 作者单位： | 同济大学,岩土及地下工程教育部重点实验室,同济大学,地下建筑与工程系,上海,200092;中国矿业大学,理学院,江苏,徐州,221008 |
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| 摘 要： | 基于金矿围岩稳定性影响指标分析,结合节点权重贡献率原理,建立BP网络模型,计算各个输入神经节点权值占整个输入神经节点权重比例大小,确定其每个影响指标对围岩分类的影响程度,按输入神经节点权重贡献率从大到小进行排序,最终确定出关键神经节点,并将其作为分类主要指标,从而提高建模精度.实验表明:这种方法用于确定金矿围岩稳定性分类指标具有较高的预测精度,能够满足分类的要求.
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| 关 键 词： | 围岩稳定性 权重贡献率 BP网络 关键神经节点 |
| 文章编号： | 1673-0836（2007）06-1051-03 |
| 收稿时间： | 2007-08-10 |
| 修稿时间： | 2007-08-10 |
Research on Estimation of Classification Index of the Surrounding Rocks in Gold Mine |
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| WANG Xue-zhi,ZHAO Chun-feng,WANG Lian-guo. Research on Estimation of Classification Index of the Surrounding Rocks in Gold Mine[J]. Chinese Journal of Underground Space and Engineering, 2007, 3(6): 1051-1053,1068 |
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| Authors: | WANG Xue-zhi ZHAO Chun-feng WANG Lian-guo |
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| Abstract: | In this paper,based on the analysis of classification index of the surrounding rocks in Gold Mine in combination with the mechanism of the weight dedication ratio,the Back propagation-based Neural Networks model is built to calculate the weight ratio of each node.Then,the influence degree of each node is gained.On the analysis of the influence degree,the key nodes are got which can be used as the classification index.The test result shows that this method has high prediction precision and satisfies the requirement of classification. |
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| Keywords: | stability of surrounding rocks weight dedication ratio Backpropagation-based Neural Networks key neural node |
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