摘要
提出BP神经网络的分布式区域滑坡预测方法,算法设计在大数据分布式处理平台Spark下实现,通过构造包含均方误差和L2正则化的代价函数,提高运算实时性和算法泛化能力。统计影响滑坡评价因子的量化指标和定义监测剖面危险级别评价值,并进行评价因子特征选取,用于三峡库区忠县区域9个滑坡11年月监测海量数据挖掘,对研究区所有滑坡监测剖面每月进行危险级别评价,实现以月为周期的区域滑坡危险程度空间预测。试验表明,采用所述方法得到的拟合精度、准确度、效率均比梯度提升决策树、随机森林算法好,预测的滑坡危险级别准确,该方法可作为区域滑坡空间预测的一种新思路。
Landslides have characteristics such as regionality, multipleness, and seriousness. The traditional area landslide spatial prediction method, under massive data condition, has poor real-time performance and strong subjectivity, and the evaluation performance is poor under multiple factors. A distributed regional landslide prediction method based on BP neural network is proposed in this paper. The algorithm is designed as a parallel computing environment of big data processing platform Spark, and the cost function of BP network is designed as two items of mean square error and L2 regularization, which improves generalization ability. Through statistics of the quantitative indicators of landslide factors and the definition of hazard index of monitoring profile, the influencing factors are selected. This approach is applied to massive data mining of 9 landslides in 11 years in Zhongxian area of Three Gorges Reservoir area, which achieves the combination of qualitative analysis and quantitative analysis. All the landslide monitoring sections in the study area were monthly evaluated to determine the risk level, and the spatial prediction of the monthly landslide risk degree was achieved. Experiments show that the fitting accuracy and efficiency obtained by the method are better than gradient-based decision trees and random forest algorithms, and the prediction area landslide risk assessment accuracy is good. This method can be used as a new approach for regional landslide spatial prediction.
作者
赵久彬
刘元雪
刘娜
胡明
ZHAO Jiu-bin;LIU Yuan-xue;LIU Na;HU Ming(Chongqing Key Laboratory of Geomechanics and Geoenvironment Protection, Army Logistics University of PLA, Chongqing 401311, China;Chongqing Testing Center of Geology and Mineral Resources, Chongqing 400042, China)
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2019年第7期2866-2872,共7页
Rock and Soil Mechanics
基金
国家自然科学基金项目(No.41877219)
重庆市基础科学与前沿技术研究专项重点项目(No.cstc2015jcyjBX0073)
重庆市国土资源和房屋管理局科技计划项目(No.KJ-2018016)
陆军勤务学院研究生创新项目(No.LY180510)~~
作者简介
第一作者简介:赵久彬,男,1987年生,博士研究生,主要从事滑坡监测预警大数据系统研究。E-mail: 459694118@qq.com;通讯作者:刘元雪,1969年生,男,博士,教授,博士生导师,主要从事岩土体本构关系与地下工程稳定性的教学与科研工作。E-mail: lyuanxue@vip.sina.com.
