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基于MRVM的多输出边坡变形预测模型
引用本文:罗亦泳,姚宜斌,王 亚.基于MRVM的多输出边坡变形预测模型[J].大地测量与地球动力学,2017,37(12):1239-1242.
作者姓名:罗亦泳  姚宜斌  王 亚
摘    要:为解决多输出边坡变形预测问题,提高预测模型的精度及计算效率,提出基于多输出相关向量机(MRVM)的边坡变形预测新模型。通过将标准RVM的单输出功能拓展到多维输出功能的方式建立MRVM,并利用PSO算法优化其参数。以某大型干坞边坡变形为例,基于MRVM建立边坡坡顶水平变形与沉降变形预测模型,并对其精度及计算效率进行分析。实验结果表明,MRVM的精度高于BP神经网络、支持向量机(SVM)、RVM,证实拓展RVM所采用的方法可行,并具有较好的边坡预测精度;MRVM的计算时间远小于BP神经网络、支持向量机(SVM)、RVM,具有较高的计算效率,并简化了建模程序,实现了对边坡的多个变形量进行同时预测。

关 键 词:边坡变形  相关向量机  多输出  精度分析  

Multi Output Slope Deformation Model Based on Multi-Output Relevance Vector Machine
LUO Yiyong,YAO Yibin,WANG Ya.Multi Output Slope Deformation Model Based on Multi-Output Relevance Vector Machine[J].Journal of Geodesy and Geodynamics,2017,37(12):1239-1242.
Authors:LUO Yiyong  YAO Yibin  WANG Ya
Abstract:In order to solve the problem of multi output slope deformation prediction,and improve the accuracy and computational efficiency of the slope deformation prediction model, a prediction model of slope deformation based on multi-output relevance vector machine(MRVM) is proposed. MRVM is established through the improvement of the output function of RVM. In order to improve the prediction accuracy of MRVM, the parameters of MRVM are optimized based on PSO.Taking the slope deformation of a large-scale dry-dock as an example,the horizontal deformation and settlement deformation of slope is predicted based on MRVM. The accuracy and computational efficiency of the model are analyzed. The experimental results show that the accuracy of MRVM is higher than that of BP neural network, support vector machine (SVM), RVM. It is proven that the expanding method of RVM is feasible, and MRVM has excellent prediction accuracy. The calculation time of MRVM is less than that of BP neural network, support vector machine (SVM), RVM. By using the above method, the repeated modeling can be avoided to improve the computational efficiency and simplify the modeling difficulty. Finally, multiple deformation of slope is predicted based on MRVM at the same time.
Keywords:   slope deformation  relevance vector machine  multi-output  accuracy analysis  
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