SVM Prediction Model of Tunnel Blasting Excavation for the Destruction of the Ancient Great Wall
Taking the blasting excavation of a highway tunnel engineering in Shanxi Province as an example,using the principle of support vector machine (SVM) learning,with aperture,hole depth,hole spacing and row spacing,the maximal segment charge,total quantity and distance from an explosive source as the main factors influencing the blasting vibration,SVM model is built.To predict respectively the particle radial,tangential and vertical direction of the peak vibration velocity and frequency,the prediction results were compared with the measured values.The experimental results show that SVM prediction model predict the peak velocity and frequency of blasting vibration,it has fast convergence,high precision,small error characteristics.The model can be used to accurately forecast blasting vibration parameters,according to the forecast results can be better to take measures to protect the ancient Great Wall.
tunnel engineering the ancient Great Wall blast vibration SVM
LI Longfu CHEN Nengge ZHANG Xiliang JIANG Dongping
Maanshan Kuangyuan Blasting Engineering Co.,Ltd.,Maanshan,Anhui,China;Maanshan Iron and Steel Group Maanshan Iron and Steel Group Mining Co.,Ltd.,Maanshan,Anhui,China Maanshan Kuangyuan Blasting Engineering Co.,Ltd.,Maanshan,Anhui,China;State Key Laboratory of Safety
国际会议
The 4th Asian-Pacific Symposium on Blasting Techniques(第四届亚洲太平洋地区爆破技术研讨会)
深圳
英文
511-515
2014-11-01（万方平台首次上网日期，不代表论文的发表时间）