,
pages 1-18
A two-step data-driven method for predicting the wear of train wheel treads using GA-BPNN and LSTM algorithms
Publication type: Journal Article
Publication date: 2024-03-02
scimago Q1
wos Q2
SJR: 0.991
CiteScore: 7.8
Impact factor: 3.6
ISSN: 23248378, 23248386
Mechanics of Materials
Automotive Engineering
Transportation
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Metrics
6
Total citations:
6
Citations from 2024:
6
(100%)
Cite this
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RIS |
BibTex
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GOST
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Liu S. et al. A two-step data-driven method for predicting the wear of train wheel treads using GA-BPNN and LSTM algorithms // International Journal of Rail Transportation. 2024. pp. 1-18.
GOST all authors (up to 50)
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Liu S., He Q., Fu W., Feng Q. A two-step data-driven method for predicting the wear of train wheel treads using GA-BPNN and LSTM algorithms // International Journal of Rail Transportation. 2024. pp. 1-18.
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RIS
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TY - JOUR
DO - 10.1080/23248378.2024.2324092
UR - https://doi.org/10.1080/23248378.2024.2324092
TI - A two-step data-driven method for predicting the wear of train wheel treads using GA-BPNN and LSTM algorithms
T2 - International Journal of Rail Transportation
AU - Liu, Saisai
AU - He, Qixin
AU - Fu, Wenjie
AU - Feng, Qibo
PY - 2024
DA - 2024/03/02
PB - Taylor & Francis
SP - 1-18
SN - 2324-8378
SN - 2324-8386
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2024_Liu,
author = {Saisai Liu and Qixin He and Wenjie Fu and Qibo Feng},
title = {A two-step data-driven method for predicting the wear of train wheel treads using GA-BPNN and LSTM algorithms},
journal = {International Journal of Rail Transportation},
year = {2024},
publisher = {Taylor & Francis},
month = {mar},
url = {https://doi.org/10.1080/23248378.2024.2324092},
pages = {1--18},
doi = {10.1080/23248378.2024.2324092}
}