基于GA-SVM的煤矿岩巷爆破效果智能预测

doi:10.11799/ce201905034

Abstract

Abstract: Prediction of blasting effect of rock roadway in the coal mine is of great significance for rational optimization of blasting parameters and improvement of blasting efficiency. Aiming at the key technical problems such as many factors affecting the blasting effect of rock roadway in the coal mine, which are difficult to accurately predict the blasting effect, a prediction model of blasting effect based on GA-SVM fusion technology is proposed to realize scientific and reasonable prediction of blasting effect. Firstly, based on a comprehensive analysis and expert scoring method, the key impact indicators affecting the blasting effect of coal mine rock roadway were determined. Secondly, according to typical cases in different mining areas, the sample database of blasting effect prediction was established and the samples were processed. Thirty sets of data were used for training, and the other 12 groups were used for prediction, the prediction accuracy was about 92%. Finally, the prediction model has been applied to practical projects. The predicted results coincided with the actual classification of blasting. The research results can provide a new idea for roadway blasting prediction.

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URL: http://www.coale.com.cn/EN/10.11799/ce201905034

http://www.coale.com.cn/EN/Y2019/V51/I5/148

References 14

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Intelligent Prediction of Blasting Effect of Coal Mine Roadway Based on GA-SVM

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