摘要
地铁轨道结构变形是影响地铁安全运营的重要因素,尤其是在沉降变形方面,因此监测地铁轨道沉降变形,同时根据监测结果对轨道的沉降变形趋势进行准确判断具有重要意义。本文以某市地铁2号线轨道监测数据为例,发挥小波分析与极限学习机(ELM)模型在数据处理、数据预测中的优势,将粒子群优化(PSO)算法用于ELM模型参数优化中,构建基于小波去噪的PSO-ELM组合预测模型,进行地铁轨道的沉降变形预测研究。通过小波分析进行监测数据去噪,解决了监测数据不稳定带来的预测结果的干扰问题;通过构建PSO-ELM组合预测模型,解决了模型参数选取随机性带来的预测精度受限问题。本文将提出的小波去噪PSO-ELM模型与单一ELM模型、小波去噪ELM模型的沉降预测结果进行对比分析,结果表明本文提出的组合预测模型预测精度最高,同时预测误差不会随预测期数的增加产生明显变化,具有较高的稳健性与适应性。
The deformation of the subway track structure is an important factor affecting the safe operation of subways,especially the settlement deformation.Therefore,monitoring the deformation of subway track settlement and accurately judging the trend of track settlement deformation based on the monitoring results are of great significance.This article took the monitoring data of subway line 2 in a city as an example and leveraged the advantages of wavelet analysis and extreme learning machine(ELM)models in data processing and prediction.The particle swarm optimization(PSO)algorithm was applied to optimize the ELM model parameters,and a PSO-ELM combined prediction model based on wavelet denoising was constructed to predict subway track settlement deformation.By using wavelet analysis to denoise monitoring data,the interference problem of prediction results caused by unstable monitoring data was solved.By constructing a PSO-ELM combined prediction model,the problem of limited prediction accuracy caused by the randomness of model parameter selection was solved.The settlement prediction results of the proposed PSO-ELM model considering wavelet denoising were compared with those of a single ELM model and ELM model considering wavelet denoising.The results show that the proposed combined prediction model has the highest prediction accuracy,and the prediction error does not change significantly with the increase in prediction periods,demonstrating high robustness and adaptability.
作者
王超
蔡足根
毛龙栋
WANG Chao;CAI Zugen;MAO Longdong(Hubei Hydrogeological Engineering Geological Survey Institute Company Limited,Wuhan,Hubei 434100,China)
出处
《北京测绘》
2024年第7期986-991,共6页
Beijing Surveying and Mapping
