Joint Prediction of Remaining Useful Life and Failure Type of Train Wheelsets: Multitask Learning Approach-Reference-Cited by-同舟云学术

Joint Prediction of Remaining Useful Life and Failure Type of Train Wheelsets: Multitask Learning Approach

Published:2018-06 Issue:6 Volume:144 Page:04018016
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Wang Weixin¹,He Qing²,Cui Yu³,Li Zhiguo⁴

Affiliation:

1. M.S. Student, Dept. of Industrial and System Engineering, Univ. at Buffalo, State Univ. of New York, 334 Bell Hall, Buffalo, NY 14260.

2. Assistant Professor, Dept. of Civil, Structural and Environmental Engineering and Dept. of Industrial and System Engineering, Univ. at Buffalo, State Univ. of New York, 313 Bell Hall, Buffalo, NY 14260 (corresponding author).

3. Ph.D. Candidate, Dept. of Civil, Structural and Environmental Engineering, Univ. at Buffalo, State Univ. of New York, 204 Ketter Hall, Buffalo, NY 14260.

4. Research Staff Member, Statistics and Data Science, IBM Thomas J. Watson Research Center, 1101 Route 134 Kichawan Rd., Yorktown Heights, NY 10598.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000113

Reference35 articles.

1. Assessing the effects of track input on the response of insulated rail joints using field experiments;Askarinejad H.;Proc. Inst. Mech. Eng. Part F,2013

2. Remaining useful life in theory and practice

3. Convex Optimization

4. A mathematical model to predict railway wheel profile evolution due to wear

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