WANG Anyi, GUO Shiku. Prediction of field intensity in mine tunnel based on LS-SVM[J]. Journal of Mine Automation, 2014, 40(10): 36-40. DOI: 10.13272/j.issn.1671-251x.2014.10.011
Citation: WANG Anyi, GUO Shiku. Prediction of field intensity in mine tunnel based on LS-SVM[J]. Journal of Mine Automation, 2014, 40(10): 36-40. DOI: 10.13272/j.issn.1671-251x.2014.10.011

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 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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