爆破震动速度峰值预测模型的比较和讨论Comparison and Discussion on Prediction Model of Blasting Peak Particle Velocity
高富强,侯爱军,杨小林
摘要(Abstract)：
传统的爆破震动峰值质点速度(PPV)预测公式已不能适应现代爆破安全的要求。基于人工神经网络(ANN)原理,建立了结构为2-5-1的BP神经网络预测模型,以青藏铁路关角隧道爆破震动测试数据为样本,对人工神经网络模型和几种传统公式的爆破震动速度预测结果进行比较。通过对实测结果与预测结果相关性系数(COD)、平均绝对误差(MAE)和相对误差(RE)的分析,表明:在传统预测模型中USBM预测公式精度最高,而人工神经网络模型较传统模型更接近实际值。
关键词(KeyWords)： 爆破震动;速度峰值预测;人工神经网络;传统预测模型
基金项目(Foundation): 国家自然基金项目(51204096);; 河南省高等学校青年骨干教师资助计划(2013GGJS-188);; 河南省科技攻关课题(112102310604;142102210569);; 河南省教育厅科学技术研究重点项目(12B130002)
作者(Author): 高富强,侯爱军,杨小林
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