Prediction of field intensity in mine tunnel based on LS-SVM
For problem of low accuracy of current prediction of field intensity in mine tunnel, a prediction model based on the least squares support vector machine method was proposed to predict the field intensity in mine tunnel by taking measured data of a tunnel as training sample. Influence of training se...
Main Authors: | , |
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Format: | Article |
Language: | zho |
Published: |
Editorial Department of Industry and Mine Automation
2014-10-01
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Series: | Gong-kuang zidonghua |
Subjects: | |
Online Access: | http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2014.10.011 |
Summary: | For problem of low accuracy of current prediction of field intensity in mine tunnel, a prediction model based on the least squares support vector machine method was proposed to predict the field intensity in mine tunnel by taking measured data of a tunnel as training sample. Influence of training set construction and parameters selection on prediction effect were analyzed in details. The simulation results show that the LS-SVM prediction model has higher prediction accuracy than dual-slope model and logarithmic correction model. |
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ISSN: | 1671-251X |