Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural Network

In order to improve the punctuality and safety of urban rail transit trains during operation and achieve accurate parking, it is necessary to track and predict the speed curve during the train operation. This paper firstly calculates the instantaneous power of the train based on the measured data, a...

Full description

Saved in:
Bibliographic Details
Main Authors: QIN Jiannan, HU Wenbin, XU Li
Format: Article
Language:zho
Published: Editorial Office of Control and Information Technology 2022-12-01
Series:Kongzhi Yu Xinxi Jishu
Subjects:
Online Access:http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2022.06.010
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849224966369705984
author QIN Jiannan
HU Wenbin
XU Li
author_facet QIN Jiannan
HU Wenbin
XU Li
author_sort QIN Jiannan
collection DOAJ
description In order to improve the punctuality and safety of urban rail transit trains during operation and achieve accurate parking, it is necessary to track and predict the speed curve during the train operation. This paper firstly calculates the instantaneous power of the train based on the measured data, and then uses the random forest model to classify the interval according to the power curve, and then establishes a real-time prediction method for the speed curve of urban rail transit trains based on neural network for different intervals. The train speed prediction model is tested. The results of model testing on the simulation data and actual line data show that the proposed algorithm can effectively predict the speed curve of the train in real time, improve the accuracy of speed tracking control. The error is reduced by 57.7% compared with the traditional neural network model, and the error is reduced by 73.9% compared with the random forest regression model.
format Article
id doaj-art-95c1bdfd5fbc41f49fa017ccf1ed3b51
institution Kabale University
issn 2096-5427
language zho
publishDate 2022-12-01
publisher Editorial Office of Control and Information Technology
record_format Article
series Kongzhi Yu Xinxi Jishu
spelling doaj-art-95c1bdfd5fbc41f49fa017ccf1ed3b512025-08-25T06:49:23ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272022-12-01626833243649Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural NetworkQIN JiannanHU WenbinXU LiIn order to improve the punctuality and safety of urban rail transit trains during operation and achieve accurate parking, it is necessary to track and predict the speed curve during the train operation. This paper firstly calculates the instantaneous power of the train based on the measured data, and then uses the random forest model to classify the interval according to the power curve, and then establishes a real-time prediction method for the speed curve of urban rail transit trains based on neural network for different intervals. The train speed prediction model is tested. The results of model testing on the simulation data and actual line data show that the proposed algorithm can effectively predict the speed curve of the train in real time, improve the accuracy of speed tracking control. The error is reduced by 57.7% compared with the traditional neural network model, and the error is reduced by 73.9% compared with the random forest regression model.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2022.06.010urban rail transit trainrandom forestneural networkspeed prediction
spellingShingle QIN Jiannan
HU Wenbin
XU Li
Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural Network
Kongzhi Yu Xinxi Jishu
urban rail transit train
random forest
neural network
speed prediction
title Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural Network
title_full Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural Network
title_fullStr Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural Network
title_full_unstemmed Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural Network
title_short Speed Prediction of Urban Rail Transit Trains Based on Random Forest & Neural Network
title_sort speed prediction of urban rail transit trains based on random forest amp neural network
topic urban rail transit train
random forest
neural network
speed prediction
url http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2022.06.010
work_keys_str_mv AT qinjiannan speedpredictionofurbanrailtransittrainsbasedonrandomforestampneuralnetwork
AT huwenbin speedpredictionofurbanrailtransittrainsbasedonrandomforestampneuralnetwork
AT xuli speedpredictionofurbanrailtransittrainsbasedonrandomforestampneuralnetwork