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A Machine Learning Approach for Predicting Railway In-Train Forces from ATO Measurements

Title:	A Machine Learning Approach for Predicting Railway In-Train Forces from ATO Measurements
Authors:	Zhang, Sheng^Aff14; Huang, Pu^Aff15; Constable, Tim^Aff15; Yan, Wenyi^Aff14
Contributors:	Chaari, Fakher, Series Editor^Aff1; Gherardini, Francesco, Series Editor^Aff2; Ivanov, Vitalii, Series Editor^Aff3; Haddar, Mohamed, Series Editor^Aff4; Cavas-Martínez, Francisco, Editorial Board Member^Aff5; di Mare, Francesca, Editorial Board Member^Aff6; Kwon, Young W., Editorial Board Member^Aff7; Tolio, Tullio A. M., Editorial Board Member^Aff8; Trojanowska, Justyna, Editorial Board Member^Aff9; Schmitt, Robert, Editorial Board Member^Aff10; Xu, Jinyang, Editorial Board Member^Aff11; Huang, Wei, editor^Aff12; Ahmadian, Mehdi, editor^Aff13
Source:	Advances in Dynamics of Vehicles on Roads and Tracks III : Proceedings of the 28th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2023, August 21–25, 2023, Ottawa, Canada - Volume 1: Rail Vehicles. :16-22
Database:	Springer Nature eBooks