A machine learning based voting regression method for adhesion estimation in wheel-rail contact

IF 3.5 2区工程技术 Q1 ENGINEERING, MECHANICAL

Vehicle System Dynamics Pub Date : 2024-08-13 DOI:10.1080/00423114.2024.2390578

Abdulkadir Zirek, Can Uysal

引用次数: 0

Abstract

The majority of control methodologies for railway vehicles depend on adhesion data to attain optimal traction. Therefore, researchers have been actively investigating practical and feasible approac...

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基于机器学习的投票回归法，用于估算轮轨接触时的附着力

铁路车辆的大多数控制方法都依赖于附着力数据来获得最佳牵引力。因此，研究人员一直在积极研究切实可行的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Vehicle System Dynamics 工程技术-工程：机械

CiteScore

8.40

自引率

13.90%

发文量

110

审稿时长

3 months

期刊介绍： Vehicle System Dynamics is an international journal, providing a source of information for the vehicle engineer and the applied scientist. The journal emphasizes the theoretical background of research and development problems of all kinds of road, rail and other ground-based vehicles. Main topics are: Dynamics of vehicle systems and their components including suspension, steering, braking, chassis systems, noise-vibration-harshness, power train; Control of motion and forces affecting vehicle behaviour; Computer aided modelling and simulation, validation, parameter identification and testing, driver modelling; Vehicle interactions with the environment including wheel-rail and tyre-ground behaviour; Active Safety Systems including collision and derailment warning, avoidance and mitigation; Intelligent vehicles, guided vehicles, automated traffic systems related to vehicle dynamics, unconventional vehicles.