Probabilistic outlier detection for robust regression modeling of structural response for high-speed railway track monitoring
| Author(s): |
Qi Li
(Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, School of Civil Engineering, Harbin Institute of Technology, Harbin, China)
Jingze Gao (Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, School of Civil Engineering, Harbin Institute of Technology, Harbin, China) James L. Beck (Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA) Chao Lin (China Railway Siyuan Survey and Design Group Co., Ltd., WuHan, China) Yong Huang
(Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, School of Civil Engineering, Harbin Institute of Technology, Harbin, China)
Hui Li
(Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, School of Civil Engineering, Harbin Institute of Technology, Harbin, China)
|
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | Structural Health Monitoring, July 2023, n. 2, v. 23 |
| Page(s): | 1280-1296 |
| DOI: | 10.1177/14759217231184584 |
- About this
data sheet - Reference-ID
10739187 - Published on:
03/09/2023 - Last updated on:
25/04/2024
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