摘要
为准确地对爆破施工引起的地面振动进行预测,结合2个隧道爆破工程实例,引入基于粒子群算法的指数型计算模型,并对计算数据进行归一化处理;以实测结果与预测结果的相对误差平方和作为适应度函数开展粒子群智能优化计算,并与2种传统的预测模型进行数据对比。结果表明,通过引入的预测方法所得到的相关系数更接近于1;均方根差最小,预测精度更佳。可为类似爆破振动预测工作提供一定的理论借鉴。
In order to accurately predict the ground vibration caused by blasting operation,combining two tunnel blasting engineering examples an exponential calculation model based on particle swarm algorithm is introduced,and the calculation data is normalized at the same time.The particle swarm optimization calculation is carried out with the relative error square sum of the actual measurement result and the prediction result as the fitness function,and the calculated results are compared with those of the 2 traditional prediction models.The results show that the correlation obtained by the prediction method introduced is the closest to 1,and the root mean square error is the least,which means the prediction accuracy is the best.The intelligent prediction method can provide a certain theoretical reference for similar blasting vibration prediction.
作者
梁娟
LIANG Juan(School of Electronic and Information Engineering,Wuhan Communications Vocational College,Wuhan 430065,China)
出处
《工程爆破》
CSCD
北大核心
2022年第3期117-121,136,共6页
Engineering Blasting
关键词
粒子群算法
爆破振动速度
智能预测
particle swarm algorithm
blasting vibration velocity
intelligent prediction
