Data-driven approaches for modeling train control models: Comparison and case studies-Reference-Cited by-同舟云学术

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Data-driven approaches for modeling train control models: Comparison and case studies

Published:2020-03 Issue: Volume:98 Page:349-363
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Yin Jiateng,Su Shuai,Xun Jing,Tang Tao,Liu Ronghui

Funder

National Natural Science Foundation of China

Beijing Jiaotong University Education Foundation

China Postdoctoral Science Foundation

Royal Academy of Engineering

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Reference44 articles.

1. Research and development of automatic train operation for railway transportation systems: A survey;Yin;Transp Res C,2017

2. Observer-based fuzzy adaptive event-triggered control for pure-feedback nonlinear systems with prescribed performance;Qiu;IEEE Trans Fuzzy Syst,2019

3. Impacts of unattended train operations on productivity and efficiency in metropolitan railways;Cohen;Transp Res Rec: J Transp Res Board,2015

4. Train energy and dynamics simulator (teds)-a state-of-the-art longitudinal train dynamics simulator;Andersen,2012

5. Development, evaluation, and comparison of acceleration models;Bham,2002

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