基于NPCA-GA-BP神经网络的采场稳定性预测方法
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谢饶青,陈建宏,肖文丰
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Prediction Method of Stope Stability Based on NPCA-GA-BP Neural Network
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Raoqing XIE,Jianhong CHEN,Wenfeng XIAO
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表4 前4个主成分及其累计贡献率
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Table 4 The first four principal component and its accumulated contribution rate
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因素 | Y1 | Y2 | Y3 | Y4 |
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X1 | 0.133 | 0.497 | -0.420 | -0.212 | X2 | 0.064 | 0.008 | -0.058 | 0.072 | X3 | -0.032 | -0.007 | -0.024 | -0.086 | X4 | 0.040 | 0.544 | 0.641 | 0.165 | X5 | -0.002 | -0.212 | 0.131 | -0.882 | X6 | 0.113 | 0.587 | -0.319 | -0.168 | X7 | 0.054 | 0.119 | 0.378 | -0.170 | X8 | 0.035 | 0.084 | 0.380 | -0.157 | X9 | 0.970 | -0.146 | 0.041 | 0.015 | X10 | 0.136 | -0.162 | -0.029 | 0.234 | 特征值 | 0.067 | 0.043 | 0.028 | 0.016 | 贡献率/% | 38.0 | 24.7 | 16.3 | 9.5 | 累计贡献率/% | 38.0 | 63.6 | 79.9 | 89.4 |
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