0
  • DE
  • EN
  • FR
  • International Database and Gallery of Structures

Advertisement

Maximum Gradient Decision-Making for Railways Based on Convolutional Neural Network

Author(s): (Professor, College of Civil Engineering, National Engineering Laboratory of High Speed Railway Construction, Central South Univ., Changsha 410075, China.)
(Ph.D. Candidate, College of Civil Engineering, National Engineering Laboratory of High Speed Railway Construction, Central South Univ., Changsha 410075, China.)
(Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742.)
(Associate Professor, College of Civil Engineering, National Engineering Laboratory of High Speed Railway Construction, Central South Univ., Changsha 410075, China (corresponding author).)
(Professorate Senior Engineer, China Railway First Survey and Design Institute Group Co. Ltd., Xi’an 710043, China.)
(Professorate Senior Engineer, China Railway Siyuan Survey and Design Group Co. Ltd., Wuhan 430063, China.)
(Professorate Senior Engineer, China Railway Eryuan Engineering Group Co. Ltd., Chengdu 610031, China.)
Medium: journal article
Language(s): English
Published in: Journal of Transportation Engineering, Part A: Systems, , n. 11, v. 145
Page(s): 04019047
DOI: 10.1061/jtepbs.0000272
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1061/jtepbs.0000272.
  • About this
    data sheet
  • Reference-ID
    10580370
  • Published on:
    08/03/2021
  • Last updated on:
    08/03/2021
 
Structurae cooperates with
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine