摘要
针对滑坡位移难以预测、影响因素难以选择等问题,提出一种结合了二次移动平均(DMA)法、变分模态分解(VMD)、改进灰狼优化(IGWO)算法与支持向量回归(SVR)的模型进行滑坡位移预测。首先,利用DMA提取滑坡位移趋势项和周期项,采用多项式拟合对趋势项进行预测;其次,对滑坡周期项的影响因素进行分类,采用VMD对原始影响因子序列进行分解获得最优序列;再次,提出一种结合SVR与基于改进Circle多策略的灰狼优化算法CTGWO-SVR(Circle Tactics Grey Wolf Optimizer with SVR)对滑坡周期项进行预测;最后采用时间序列加法模型求出累计位移预测序列,并采用灰色预测的后验证差校验和小概率误差对模型进行评价。实验结果表明,与GA-SVR和GWO-SVR模型相比,CTGWO-SVR的预测精度更高,拟合度达到0.979,均方根误差分别减小了51.47%与59.25%,预测精度等级为一级,可满足滑坡预测的实时性和准确性要求。
To address the issues of difficult prediction of landslide displacement and difficulty in selecting influencing factors,a model combining Double Moving Average(DMA),Variational Modal Decomposition(VMD),Improved Gray Wolf Optimizer(IGWO)algorithm and Support Vector Regression(SVR)was proposed for landslide displacement prediction.Firstly,DMA was used to extract the trend and periodic terms of landslide displacement,and polynomial fitting was used to predict the trend term.Secondly,the influencing factors of the landslide periodic term were classified,and VMD was used to decompose the original factor sequence to obtain the optimal sequence.Then,a grey wolf optimizer algorithm combining SVR with an improved Circle-based multi-tactic,called CTGWO-SVR(Circle Tactics Grey Wolf Optimizer with SVR),was proposed to predict the landslide periodic term.Finally,the cumulative displacement prediction sequence was obtained using a time series additive model,and the model was evaluated using post validation difference verification and small probability error in grey prediction.Experimental results show that compared with GA(Genetic Algorithm)-SVR and GWO-SVR models,CTGWO-SVR has higher prediction accuracy with a fitting degree of 0.979,and the Root Mean Square Error(RMSE)reduces by 51.47%and 59.25%,respectively.The model evaluation accuracy is level one,which can meet the real-time and accuracy requirements of landslide prediction.
作者
任帅
纪元法
孙希延
韦照川
林子安
REN Shuai;JI Yuanfa;SUN Xiyan;WEI Zhaochuan;LIN Zian(Guangxi Key Laboratory of Precision Navigation Technology and Application(Guilin University of Electronic Technology),Guilin Guangxi 541004,China;School of Information and Communication,Guilin University of Electronic Technology,Guilin Guangxi 541004,China;National&Local Joint Engineering Research Center of Satellite Navigation Positioning and Location Service,Guilin University of Electronic Technology,Guilin Guangxi 541004,China;GUET-Nanning E-Tech Research Institute Company Limited,Nanning Guangxi 530031,China)
出处
《计算机应用》
CSCD
北大核心
2024年第3期972-982,共11页
journal of Computer Applications
基金
国家自然科学基金资助项目(62061010,62161007)
广西科技厅项目(桂科AD20302022)。
关键词
滑坡位移预测
位移分解
时间序列
变分模态分解
灰色关联分析
灰狼优化算法
支持向量回归
landslide displacement prediction
displacement decomposition
time series
Variational Modal Decomposition(VMD)
grey correlation analysis
Gray Wolf Optimizer(GWO)algorithm
Support Vector Regression(SVR)
作者简介
任帅(2000-),男,陕西渭南人,硕士研究生,主要研究方向:滑坡灾害预警系统;通信作者:纪元法(1975-),男,山东莘县人,教授,博士,主要研究方向:卫星导航,电子邮箱jiyuanfa@163.com;孙希延(1973-),女,山东潍坊人,教授,博士,主要研究方向:卫星导航;韦照川(1973-),男,广西河池人,副教授,硕士,主要研究方向:信号处理;林子安(1991-),男,广西梧州人,博士研究生,主要研究方向:计算机图形学。
