灰色RBF在地铁沉降监测中的应用
|
摘要
随着城市发展,致使地铁沉降的因素越来越多,地铁沉降监测越来越重要。对此,本文基于灰色模型和RBF神经网络预测模型,对两者融合方法进行了研究。通过对某城市地铁沉降监测数据进行预报和分析,证明了灰色RBF神经网络模型预测精度优于单一模型预测精度,组合模型避免了灰色模型线性补偿的弊端、增加了数据利用率、增强了算法的鲁棒性,预报结果更加准确。
With the development of the city, there are more and more factors leading to the subway subsidence, and the monitoring of the subway protection area is becoming more and more important. In this paper, based on the grey model and the prediction method of RBF neural network, the fusion method of the two is studied. By forecasting and analyzing the monitoring data of subway subsidence in a certain city, it is proved that the prediction accuracy of the grey RBF neural network model is better than that of the single model.
With the development of the city, there are more and more factors leading to the subway subsidence, and the monitoring of the subway protection area is becoming more and more important. In this paper, based on the grey model and the prediction method of RBF neural network, the fusion method of the two is studied. By forecasting and analyzing the monitoring data of subway subsidence in a certain city, it is proved that the prediction accuracy of the grey RBF neural network model is better than that of the single model.
引文
[1] 赵建飞,张俊中,李东辉,等.加权GM(1.1)模型在地铁沉降监测中的应用[J].测绘与空间地理信息,2015(5):56-58.
[2] 朱军桃,李亚威,熊东旭,等.建筑物沉降监测中的改进灰色模型[J].测绘科学,2017,42(11):85-91.
[3] 刘江,王征博,刘成,等.灰色-时序组合模型在建筑沉降预测中的应用[J].北京测绘,2018,32(2):214-217.
[4] 胡海斌,郭新慧,阎跃观.灰色预计模型在煤矿沉陷区沉降预测中的应用[J].北京测绘,2017(4):1-3,18.
[5] 周志广,冀彦卓.地铁施工引发地面沉降的BP神经网络预测分析[J].地质灾害与环境保护,2014,25(3):97-102.
[6] 孙飞跃,刘清,贺琪,等.基于灰色理论的地铁沉降预测研究[J].建筑技术,2017,48(7):761-764.
[7] 吴乃龙,周永领.基于BP神经网络改进算法在地铁隧道施工中的沉降预测[J].城市勘测,2015(3):148-150,157.
[8] 周星勇.径向基神经网络在地铁沉降预测当中的应用[J].科技资讯,2017,15(20):93-94.
[9] 夏磊凯,黃其欢,夏晨翔,等.改进后灰色神经网络及短期基坑沉降预测研究[J].测绘工程,2016,25(6):56-60.
[10] 马健武.基于RBF神经网络模型的GNSS对流层延迟插值[D].安徽合肥:合肥工业大学,2018.
[11] 曾贤敏,黄腾,谢朋朋.基于并联型灰色神经网络模型的隧道沉降量预测方法探讨[J].勘察科学技术,2016(5):14-16,29.
[2] 朱军桃,李亚威,熊东旭,等.建筑物沉降监测中的改进灰色模型[J].测绘科学,2017,42(11):85-91.
[3] 刘江,王征博,刘成,等.灰色-时序组合模型在建筑沉降预测中的应用[J].北京测绘,2018,32(2):214-217.
[4] 胡海斌,郭新慧,阎跃观.灰色预计模型在煤矿沉陷区沉降预测中的应用[J].北京测绘,2017(4):1-3,18.
[5] 周志广,冀彦卓.地铁施工引发地面沉降的BP神经网络预测分析[J].地质灾害与环境保护,2014,25(3):97-102.
[6] 孙飞跃,刘清,贺琪,等.基于灰色理论的地铁沉降预测研究[J].建筑技术,2017,48(7):761-764.
[7] 吴乃龙,周永领.基于BP神经网络改进算法在地铁隧道施工中的沉降预测[J].城市勘测,2015(3):148-150,157.
[8] 周星勇.径向基神经网络在地铁沉降预测当中的应用[J].科技资讯,2017,15(20):93-94.
[9] 夏磊凯,黃其欢,夏晨翔,等.改进后灰色神经网络及短期基坑沉降预测研究[J].测绘工程,2016,25(6):56-60.
[10] 马健武.基于RBF神经网络模型的GNSS对流层延迟插值[D].安徽合肥:合肥工业大学,2018.
[11] 曾贤敏,黄腾,谢朋朋.基于并联型灰色神经网络模型的隧道沉降量预测方法探讨[J].勘察科学技术,2016(5):14-16,29.