摘要
施工仿真参数更新是确保建设期施工进度仿真准确性的关键。但现有的参数更新方法难以对参数局部非线性和波动性变化特征进行学习和提取,更新精度有待进一步提高。为此,本文利用深度学习模型能够深度挖掘参数序列隐含信息的优势,采用分解-预测-集成的建模新思路,提出高拱坝施工仿真参数EMD-P-ILSTM动态更新模型。该模型利用基于自适应步长改进的天牛须算法对长短期记忆网络模型的超参数进行自动寻优,以提高建模效率。采用经验模态分解法将参数序列分解为多个平稳的子序列,并利用偏自相关函数自动选取各子序列的时间窗口。工程实例表明,相比于未改进的LSTM、BPNN、SVM和贝叶斯更新方法,本文模型能有效跟踪施工参数的复杂变化,具有更高的预测精度。
For construction schedule simulation,parameters updating is the key to ensuringits accuracy.However,it is difficultfor its existing methods to learn and extract the local nonlinear fluctuation characteristics of the parameters,and the updating accuracy needs further improvement.This paper takes advantage of the deep learning model's capability of mining more hidden information from parameter sequencesandadopts a new modeling idea of decomposition-predict-integration.We construct a new dynamic updating model ofconstruction simulation parameters using the techniques of empirical mode decomposition,and improvedlongshort-term memory(EMD-P-ILSTM).To improve modeling efficiency,we use an improved Beetle Antennae algorithm based on an adaptive step factor to automatically optimize the hyperparameters of the LSTM network model.The EMD method is used to decompose a parameter sequence into several stationary sub-sequences;a partial autocorrelation function is used to select a time window for each sub-sequence automatically.A case study shows that,compared with the unimproved LSTM,BPNN,SVM,or Bayesian update method,our new model can track effectively the complicated changes in construction parameters and achievea higher prediction accuracy.
作者
王国浩
余佳
王晓玲
肖尧
乔雨
任炳昱
关涛
WANG Guohao;YU Jia;WANG Xiaoling;XIAO Yao;QIAO Yu;REN Bingyu;GUAN Tao(State Key Laboratory of Hydraulic Engineering Simulation and Safety,Tianjin University,Tianjin 300350;China Three Gorges Construction Engineering Corporation,Chengdu 610000)
出处
《水力发电学报》
CSCD
北大核心
2021年第12期106-118,共13页
Journal of Hydroelectric Engineering
基金
国家重点研发计划(2018YFC0406706)
国家自然科学基金(51879186)
中国长江三峡集团公司科研项目资助(WDD/0430)。
关键词
高拱坝
施工仿真参数更新
长短期记忆网络
改进天牛须算法
经验模态分解
偏自相关函数
high arch dam
construction simulation parameter update
long-short-term memory network
improved Beetle Antennae algorithm
empirical mode decomposition
partial autocorrelation function
