基于GEP的爆破峰值速度预测模型

PDF(1163 KB)

振动与冲击 ›› 2015, Vol. 34 ›› Issue (10) : 95-99.

论文

基于GEP的爆破峰值速度预测模型

史秀志1，陈新1，史采星1，刘博1，张迅2

作者信息 +

Prediction of blasting-vibration-peak-speed by GEP

SHI Xiu-zhi1，CHEN Xin1，SHI Cai-xing1，LIU Bo1，ZHANG Xun2

Author information +

文章历史 +

摘要

针对施工中爆破振动危害严重、振动峰值速度难以预测问题，选用基因表达式编程（Gene Expression Programming， GEP）算法以MyEclipse为开发工具，建立基于GEP的爆破峰值速度预测模型。取实测数据进行预测，并与萨道夫斯基经验公式与模糊神经网络模型预测结果对比。结果表明，三者平均相对误差分别为8.8%、11.3%及27.9%。由此证明GEP模型预测爆破峰值速度可行，亦为爆破振动预测提供新思路。

Abstract

In order to predict the peak particle velocity of blasting vibration, this paper select the measured data of an open pit bench blasting and established a prediction model of peak particle velocity of blasting vibration based on GEP with Eclipse as a development tool to simulating the date. By comparing the forecast value and the measured value, the average relative error of the three results (GEP, fuzzy-neural network and experience formula) respectively are 8.8%, 11.3% and 27.9%. Predicted results demonstrate the GEP is a feasible tool and a new idea to predict the peak particle velocity of blasting vibration.

导出引用

史秀志1，陈新1，史采星1，刘博1，张迅2. 基于GEP的爆破峰值速度预测模型[J]. 振动与冲击, 2015, 34(10): 95-99

SHI Xiu-zhi1，CHEN Xin1，SHI Cai-xing1，LIU Bo1，ZHANG Xun2. Prediction of blasting-vibration-peak-speed by GEP[J]. Journal of Vibration and Shock, 2015, 34(10): 95-99

参考文献

[1] 史秀志,林大能,陈寿如. 基于粗糙集模糊神经网络的爆破振动危害预测[J].爆炸与冲击,2009, 29 (4): 401-407.
     SHI Xiu-zhi, LIN Da-neng, CHEN Shou-ru. Blasting vibration induced damage prediction by rough set based fuzzy-neural network[J]. Explosion and Shock Waves, 2009, 29 (4): 401-407.
[2] 唐海,石永强,李海波,等. 基于神经网络的爆破振动速度峰值预报[J].岩石力学与工程学报,2007, 26(增1):3533-3539.
     TANG Hai, SHI Yong-qiang, LI Hai-bo, et al. Prediction of peak particle velocity of blasting vibration by neural network [J].Rock mechanics and Engineering, 2007, 26(S1):3533- 3539.
[3] 方向,陆凡东,高振儒,等. 中深孔爆破振动加速度峰值的遗传BP网络预测[J]. 解放军理工大学学报(自然科学版)，2010, 11(3):312-315.
     FANG Xiang, LU Fan-dong, GAO Zhen-ru, et al. A BP neural network model for forecasting of blasting vibration acceleration peak value from deep hole blasting[J].Journal of PLA university of science and technology: Natural Science Edition , 2010, 11(3):312-315.
[4] 李菁,马彦琳,梁晓群. 基于基因表达式编程的电力消费预测模型-武汉市的实证[J]. 统计研究,2008, 25(4): 45-49.
     LI Jing, MA Yan-lin, LIANG Xiao-qun. Prediction of Wuhan’ power consumption by gene expression programming[J]. Statistical Research, 2008, 25 (4): 45-49.
[5] 杨晶,胡珉,吴耿峰. 基因表达式编程算法的改进及其应用研究[J]. 计算机工程与应用,2007, 43(6): 240-243.
     YANG Jing, HU Min, WU Geng-feng. Improvement and application of gene expression programming[J]. Computer Engineering and Applications, 2007, 43(6): 240-243.
[6] 刘桂琴. GEP在演化建模中的应用[D].武汉：华中师范大学,2009: 9-12.
[7] 袁晖,元昌安,覃晓,等. 基于GEP自动聚类算法的视频关键帧提取方法[J].广西师范学院(自然科学版),2013,30(1): 98-101.
YUAN Hui, YUAN Chang-an, QIN Xiao, et al. A method of video key frame extraction based on GEP automatic clustering algorithm[J]. Journal of Guangxi Teachers Education University(Natural Science Edition), 2013, 30 (1): 98-101.
[8] 王超,赵延军,董卓. GEP算法在变压器故障诊断中的应用研究[J].技术应用，2012, 60(3): 60-71.
     WANG Chao, ZHAO Yan-jun, DONG Zhuo. Research on   application of GEP algorithm in transformer fault diagnosis [J]. Journal of Communicate Technology, 2012, 60(3): 60-71.
[9] 杜冬，麦海波. 基于GEP的四维飞行轨迹预测模型[J].四川大学学报(自然科学版),2013, 50(4): 749-752.
     DU Dong, MAI Hai-bo. 4-D trajectory prediction model based on GEP[J]. Journal of Sichuan University(Natural Science Edition), 2013, 50(4): 749-752.
[10] 孟艳,赵洪波,茹忠亮,等. GEP在桁架结构优化中的应用[J].工程力学,2013, 30(1): 237-241.
MENG Yan, ZHAO Hong-bo, RU Zhong-liang, et al. The application of GEP in truss structure optimization[J]. Engineering Mechanics, 2013, 30(1): 237-241.
[11] 古玲岚. 基于GEP-RBF的协同过滤数据稀疏性问题研究[J].计算机与数字工程,2013, 9: 1432-1436.
      GU Ling-lan. Data sparse issue of collaborative filtering algorithm based on GEP-RBF[J]. Computer and Digital Engineering, 2013, 9: 1432-1436.
[12] 刘萌伟,黎夏,刘涛. 基于基因表达式编程的人口预测模型[J]. 中山大学学报(自然科学版),2010, 49(6): 116-120.
LIU Meng-wei, LI Xia, LIU Tao. A gene expression programming algorithm for population prediction problems [J]. Journal of Sun Yatsen University(Natural Science Edition), 2010, 49(6): 116-120.
[13] 陈毅,杨一洋. 基于基因表达式编程的大坝位移强度聚类分析研究[J]. 测绘与空间地理信息,2013, 36(9): 33-36.
      CHEN Yi, YANG Yi-yang. Study on clister analysis of dam deformation displacement intensity based on gene expression programming algorithm[J]. Geomatics and Spatial Information Technology,2013, 36(9): 33-36.
[14] 刘传立,刘小生,李妍妍. 基于GEP的金属矿尾矿坝变形预测模型研究[J]. 有色金属科学与工程，2013, 6: 63-68.
      LIU Chuan-li, LIU Xiao-sheng, LI Yan-yan. Research on deformation prediction model of metal mine tailings dam based on GEP[J]. Nonferrous Metals Science and Engineering, 2013, 6: 63-68.
[15] 史秀志. 爆破振动信号时频分析与爆破振动特征参量和危害预测研究[D].长沙：中南大学，2007: 93-115.
[16] 刘博,史秀志,黄宣东,等. 基于拟牛顿法的QN-BP预测爆破振动峰值速度[J].中国有色金属学报,2013,23(5): 1428-1433.
LIU Bo, SHI Xiu-zhi, HUANG Xuan-dong, et al. Prediction of peak particle velocity of blasting vibration by QN-BP based on Quasi-Newton method [J]. The Chinese Journal of Nonferrous Metals, 2013, 23(5): 1428-1433.
[17] Shi Xiu-zhi, Zhou Jian, Wu Bang-biao, et al. Support vector machines approach to mean particle size of rock fragmentation due to bench blasting prediction[J]. Transactions of Nonferrous Metals society of China, 2012, 22(2): 432-441.