Prediction of train wheel diameter based on Gaussian process regression optimized using a fast simulated annealing algorithm.
An algorithm to predict train wheel diameter based on Gaussian process regression (GPR) optimized using a fast simulated annealing algorithm (FSA-GPR) is proposed in this study to address the problem of dynamic decrease in wheel diameter with increase in mileage, which affects the measurement accura...
Saved in:
| Main Authors: | Xiaoying Yu, Hongsheng Su, Zeyuan Fan, Yu Dong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2019-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0226751&type=printable |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Wheel-rail Contact Relation Based on Different Wheel Diameter
by: ZHANG Maosong, et al.
Published: (2016-01-01) -
Uncertain data analysis algorithm based on fast Gaussian transform
by: Rong-hua CHI, et al.
Published: (2017-03-01) -
Uncertain data analysis algorithm based on fast Gaussian transform
by: Rong-hua CHI, et al.
Published: (2017-03-01) -
A Method of Locomotive Automatic Wheel Diameter Correction Based on GPS Speed
by: Fan JIANG, et al.
Published: (2019-03-01) -
Fast Perfekt: Regression-based refinement of fast simulation
by: Moritz Wolf, Lars O. Stietz, Patrick L. S. Connor, Peter Schleper, Samuel Bein
Published: (2025-02-01)