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3 各指标之间的Pearson相关性系数
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Table 3 Pearson correlation coefficient between indicators
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因素 | X1 | X2 | X3 | X4 | X5 | X6 | X7 | X8 | X9 | X10 | X11 |
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X1 | 1.000 | 0.120 | 0.071 | 0.163 | -0.108 | 0.746 | -0.130 | -0.168 | 0.231 | -0.205 | -0.004 | X2 | 0.120 | 1.000 | 0.228 | -0.036 | -0.175 | 0.223 | -0.151 | -0.183 | 0.227 | 0.181 | 0.052 | X3 | 0.070 | 0.228 | 1.000 | -0.016 | 0.176 | 0.086 | 0.031 | 0.002 | -0.169 | -0.247 | 0.250 | X4 | 0.160 | -0.036 | -0.016 | 1.000 | -0.112 | 0.253 | 0.531 | 0.497 | 0.015 | -0.199 | -0.551 | X5 | -0.100 | -0.175 | 0.176 | -0.112 | 1.000 | -0.186 | 0.209 | 0.142 | 0.141 | -0.033 | 0.047 | X6 | 0.740 | 0.223 | 0.086 | 0.253 | -0.186 | 1.000 | 0.074 | 0.017 | 0.134 | -0.197 | -0.250 | X7 | -0.130 | -0.151 | 0.031 | 0.531 | 0.209 | 0.074 | 1.000 | 0.907 | 0.101 | -0.078 | -0.633 | X8 | -0.160 | -0.183 | 0.002 | 0.497 | 0.142 | 0.017 | 0.907 | 1.000 | 0.046 | -0.142 | -0.602 | X9 | 0.230 | 0.227 | -0.169 | 0.015 | 0.141 | 0.134 | 0.101 | 0.046 | 1.000 | 0.391 | -0.229 | X10 | -0.200 | 0.181 | -0.247 | -0.199 | -0.033 | -0.197 | -0.078 | -0.142 | 0.391 | 1.000 | -0.063 | X11 | -0.004 | 0.052 | 0.250 | -0.551 | 0.047 | -0.250 | -0.633 | -0.602 | -0.229 | -0.063 | 1.000 |
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