Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU
Abstract Due to the complexity and variability of shield machine working environment, it is very important to accurately control and regulate the position trajectory of shield machine. For that reason, an intelligent real-time prediction model of shield machine position based on BWO-LSTM-GRU (Beluga...
Published in: | Engineering Research Express |
---|---|
Main Authors: | , , , |
Other Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | unknown |
Published: |
IOP Publishing
2024
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1088/2631-8695/ad2b27 https://iopscience.iop.org/article/10.1088/2631-8695/ad2b27 https://iopscience.iop.org/article/10.1088/2631-8695/ad2b27/pdf |
id |
crioppubl:10.1088/2631-8695/ad2b27 |
---|---|
record_format |
openpolar |
spelling |
crioppubl:10.1088/2631-8695/ad2b27 2024-06-02T08:04:17+00:00 Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU Xuanyu, Liu Mengting, Jiang Wenshuai, Zhang Yudong, Wang Scientific Research Fund Program of The Educational Department of Liaoning Province of China The Basic Scientific Research Program of The Educational Department of Liaoning Province of China—General Program 2024 http://dx.doi.org/10.1088/2631-8695/ad2b27 https://iopscience.iop.org/article/10.1088/2631-8695/ad2b27 https://iopscience.iop.org/article/10.1088/2631-8695/ad2b27/pdf unknown IOP Publishing https://iopscience.iop.org/page/copyright https://iopscience.iop.org/info/page/text-and-data-mining Engineering Research Express volume 6, issue 1, page 015105 ISSN 2631-8695 journal-article 2024 crioppubl https://doi.org/10.1088/2631-8695/ad2b27 2024-05-07T14:03:00Z Abstract Due to the complexity and variability of shield machine working environment, it is very important to accurately control and regulate the position trajectory of shield machine. For that reason, an intelligent real-time prediction model of shield machine position based on BWO-LSTM-GRU (Beluga whale optimization-Long Short-term Memory-Gated recurrent unit) is proposed in this paper. Firstly, the real-time data of shield machine are processed based on Pearson correlation analysis, and the tunneling parameters presenting medium-strong correlation with the position parameters are filtered to obtain, which were used to be input variables for prediction models. Secondly, LSTM-GRU position prediction model was established separately for shield machine position parameters, and four hyperparameters of the model were optimized separately using BWO. Finally, BWO-LSTM-GRU position prediction models are used to realize the intelligent real-time prediction of the motion trajectories at four positions for shield machine. The simulation results indicate that the prediction deviation in the position prediction model is within 3 mm, and it can accurately complete the task of real-time prediction, providing real-time data support for shield machine drivers. Article in Journal/Newspaper Beluga Beluga whale Beluga* IOP Publishing Engineering Research Express 6 1 015105 |
institution |
Open Polar |
collection |
IOP Publishing |
op_collection_id |
crioppubl |
language |
unknown |
description |
Abstract Due to the complexity and variability of shield machine working environment, it is very important to accurately control and regulate the position trajectory of shield machine. For that reason, an intelligent real-time prediction model of shield machine position based on BWO-LSTM-GRU (Beluga whale optimization-Long Short-term Memory-Gated recurrent unit) is proposed in this paper. Firstly, the real-time data of shield machine are processed based on Pearson correlation analysis, and the tunneling parameters presenting medium-strong correlation with the position parameters are filtered to obtain, which were used to be input variables for prediction models. Secondly, LSTM-GRU position prediction model was established separately for shield machine position parameters, and four hyperparameters of the model were optimized separately using BWO. Finally, BWO-LSTM-GRU position prediction models are used to realize the intelligent real-time prediction of the motion trajectories at four positions for shield machine. The simulation results indicate that the prediction deviation in the position prediction model is within 3 mm, and it can accurately complete the task of real-time prediction, providing real-time data support for shield machine drivers. |
author2 |
Scientific Research Fund Program of The Educational Department of Liaoning Province of China The Basic Scientific Research Program of The Educational Department of Liaoning Province of China—General Program |
format |
Article in Journal/Newspaper |
author |
Xuanyu, Liu Mengting, Jiang Wenshuai, Zhang Yudong, Wang |
spellingShingle |
Xuanyu, Liu Mengting, Jiang Wenshuai, Zhang Yudong, Wang Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU |
author_facet |
Xuanyu, Liu Mengting, Jiang Wenshuai, Zhang Yudong, Wang |
author_sort |
Xuanyu, Liu |
title |
Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU |
title_short |
Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU |
title_full |
Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU |
title_fullStr |
Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU |
title_full_unstemmed |
Intelligent real-time prediction for shield machine position on the basis of BWO-LSTM-GRU |
title_sort |
intelligent real-time prediction for shield machine position on the basis of bwo-lstm-gru |
publisher |
IOP Publishing |
publishDate |
2024 |
url |
http://dx.doi.org/10.1088/2631-8695/ad2b27 https://iopscience.iop.org/article/10.1088/2631-8695/ad2b27 https://iopscience.iop.org/article/10.1088/2631-8695/ad2b27/pdf |
genre |
Beluga Beluga whale Beluga* |
genre_facet |
Beluga Beluga whale Beluga* |
op_source |
Engineering Research Express volume 6, issue 1, page 015105 ISSN 2631-8695 |
op_rights |
https://iopscience.iop.org/page/copyright https://iopscience.iop.org/info/page/text-and-data-mining |
op_doi |
https://doi.org/10.1088/2631-8695/ad2b27 |
container_title |
Engineering Research Express |
container_volume |
6 |
container_issue |
1 |
container_start_page |
015105 |
_version_ |
1800748904367521792 |