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金属矿山 ›› 2011, Vol. 40 ›› Issue (06): 56-58.

• 采矿工程 • 上一篇    下一篇

支持向量机预测高边坡爆破质点振动速度

欧敏,林从谋   

  1. 华侨大学岩土工程研究所
  • 出版日期:2011-06-08 发布日期:2011-06-09
  • 基金资助:

     国家自然科学基金项目(编号:50778107),福建省自然基金项目(编号:2006J0445),福建省科技重点课题项目(编号:2007H0055)。

Prediction of High Slope Blasting Vibration Based on Support Vector Machine

Ou Min,Lin Congmou   

  1. Institute of Geotechnical Engineering, Huaqiao University
  • Online:2011-06-08 Published:2011-06-09

摘要: 基于泉州某工程高岩石边坡爆破振动数据,选择单段最大药量、水平距离、高程差作为影响因子,采用支持向量机(SVM)与传统方法相结合的预测方法进行训练、交叉验证、最后预测。证明支持向量机理论能较好地预测爆破振动合速度。研究成果为改善岩石高边坡爆破振动预测精度提供了一种方法。  

关键词: 支持向量机, 预测, 质点振动峰速度

Abstract: Based on the blasting vibration data of a high rock slope in Quanzhou, and selecting the maximum dose of single-stage, horizontal distance, height difference as impact factors, the process of training and cross-validation and final prediction is made by jointing with support vector machineSVM) and traditional methods. It is confirmed that the support vector machine theory can predict the velocity of blasting vibration well. This research result provides a way to improve the prediction accuracy of blasting vibration. 

Key words: Blasting vibration, Support vector machine, Prediction, Peak particle velocity