loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Shuo Yang ; Xiaofeng Yang and Zhengnan Lin

Affiliation: School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100000, China., China

Keyword(s): Heavy Haul Train; Driving Strategy; Support Vector Regression (SVR).

Abstract: In order to reduce the labor intensity of heavy-haul train drivers in the downgrade section and near the split phase area, the paper analyzes the factors that affect the driving strategy of heavy-haul train in accordance with the manual driving strategy. In this paper, A control model of heavy-haul train electric braking force based on support vector regression (SVR) is proposed to control the electric braking force. With the manual driving records used as training data, Electric braking force and other information are extracted as output results and features to train the control model. By trial and error, parameters of the control model are adjusted to optimize the model. The results show that the control model in this paper is close to the manual driving in the same situation, which is positive for reducing the labor intensity of drivers in heavy-haul railway.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.129.19.251

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Yang, S.; Yang, X. and Lin, Z. (2020). Driving Strategy of Heavy Haul Train based on Support Vector Regression. In Proceedings of the International Symposium on Frontiers of Intelligent Transport System - FITS; ISBN 978-989-758-465-7, SciTePress, pages 70-74. DOI: 10.5220/0010121200700074

@conference{fits20,
author={Shuo Yang. and Xiaofeng Yang. and Zhengnan Lin.},
title={Driving Strategy of Heavy Haul Train based on Support Vector Regression},
booktitle={Proceedings of the International Symposium on Frontiers of Intelligent Transport System - FITS},
year={2020},
pages={70-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010121200700074},
isbn={978-989-758-465-7},
}

TY - CONF

JO - Proceedings of the International Symposium on Frontiers of Intelligent Transport System - FITS
TI - Driving Strategy of Heavy Haul Train based on Support Vector Regression
SN - 978-989-758-465-7
AU - Yang, S.
AU - Yang, X.
AU - Lin, Z.
PY - 2020
SP - 70
EP - 74
DO - 10.5220/0010121200700074
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic