Time-series prediction of shield movement performance during tunneling based on hybrid model. (January 2022)
- Record Type:
- Journal Article
- Title:
- Time-series prediction of shield movement performance during tunneling based on hybrid model. (January 2022)
- Main Title:
- Time-series prediction of shield movement performance during tunneling based on hybrid model
- Authors:
- Lin, Song-Shun
Zhang, Ning
Zhou, Annan
Shen, Shui-Long - Abstract:
- Highlights: A framework about automatic data collection and application of developed model during tunneling is presented. Hybrid model is developed based on PSO and LSTM neural network. The developed model is utilized to predict the main thrust. Developed model provides a reference in operational variables' regulation. Abstract: This study presents a hybrid model based on the particle swarm optimization (PSO) algorithm and a long short-term memory (LSTM) neural network. PSO can determine the hyperparameters for the LSTM neural network. Using this approach, a framework for automatic data collection and application of the developed model during tunnel excavation was explored. The proposed model includes three stages: (i) data collection and pre-processing, (ii) hybrid prediction model establishment, and (iii) model performance validation. Pearson correlation coefficient is adopted to analyze the relationships between the influential factors and predicted object, which aids in feature selection for the developed model. A total of 1500 data sets, from a tunnel construction case in Shenzhen, China, were collected for training and testing the hybrid model. The results showed that the hybrid model with all the influential factors yielded the best performance. Thus, the developed model can provide a guideline for coping with measured data from an automatic monitoring system in earth pressure balance shield machines.
- Is Part Of:
- Tunnelling and underground space technology. Volume 119(2022)
- Journal:
- Tunnelling and underground space technology
- Issue:
- Volume 119(2022)
- Issue Display:
- Volume 119, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 119
- Issue:
- 2022
- Issue Sort Value:
- 2022-0119-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-01
- Subjects:
- Shield tunneling -- Time series prediction -- Feature selection -- Long-short term neural network -- Hybrid model
Tunneling -- Periodicals
Underground construction -- Periodicals
Tunnels -- Periodicals
Underground areas -- Periodicals
624.193 - Journal URLs:
- http://www.sciencedirect.com/science/journal/08867798 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tust.2021.104245 ↗
- Languages:
- English
- ISSNs:
- 0886-7798
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9071.405000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20101.xml