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基于BP神经网络的高含水岩石爆破震动参数预报
引用本文:李玉能,马建军,池恩安,陈永麟. 基于BP神经网络的高含水岩石爆破震动参数预报[J]. 爆破, 2017, 34(2). DOI: 10.3963/j.issn.1001-487X.2017.02.013
作者姓名:李玉能  马建军  池恩安  陈永麟
作者单位:武汉科技大学 理学院,武汉 430081;贵州新联爆破工程集团有限公司,贵阳 550000;武汉科技大学 理学院,武汉,430081;贵州新联爆破工程集团有限公司,贵阳,550000
基金项目:黔科合支撑[2016]2312
摘    要:运用现场试验震动监测得出水介质对高含水岩石爆破地震波传播规律的影响,再结合BP神经网络理论,将水介质纳入网络模型,建立爆破震动参数预报的BP神经网络模型。采用高含水岩石爆破现场监测数据对网络模型进行训练。把训练达到最优后的预报结果与实测结果作对比,发现BP神经网络模型预报参数与实测值较为接近。

关 键 词:高含水岩石  BP神经网络  爆破震动  预报模型

Forecast of Blasting Vibration Parameters in High Water Cut Rock based on BP Neural Network
LI Yu-neng,MA Jian-jun,CHI En-an,CHEN Yong-lin. Forecast of Blasting Vibration Parameters in High Water Cut Rock based on BP Neural Network[J]. Blasting, 2017, 34(2). DOI: 10.3963/j.issn.1001-487X.2017.02.013
Authors:LI Yu-neng  MA Jian-jun  CHI En-an  CHEN Yong-lin
Abstract:The influence of water medium on the propagation law of blasting vibration in high water cut rock is studied by vibration monitoring in field test.Combining with the BP neural network theory,the water medium is incorporated into the network model to establish the blasting vibration parameter forecasting model.The network model is trained by using site monitoring data of high water cut rock blasting.The optimum results of BP neural network model after training are compared with the measured data.It is found that the BP neural network model is close to the measured value,which is instructive for such engineering blasting.
Keywords:high water cut rock  BP neural network  blasting vibration  forecasting model
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