Temperature field test and prediction using a GA-BP neural network for CRTS II slab tracks

IF 4.4 1区工程技术 Q2 TRANSPORTATION SCIENCE & TECHNOLOGY

Railway Engineering Science Pub Date : 2023-07-03 DOI:10.1007/s40534-023-00309-1

Dan Liu, Chengguang Su, Rong-shan Yang, J. Ren, Xue-yi Liu

引用次数: 0

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基于GA-BP神经网络的CRTS II平板轨道温度场测试与预测

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

Railway Engineering Science TRANSPORTATION SCIENCE & TECHNOLOGY-

CiteScore

10.80

自引率

7.90%

发文量

1061

审稿时长

15 weeks

期刊介绍： Railway Engineering Science is an international, peer-reviewed, and free open-access journal that publishes original research articles and comprehensive reviews related to fundamental engineering science and emerging technologies in rail transit systems, focusing on the cutting-edge research in high-speed railway, heavy-haul railway, urban rail transit, maglev system, hyperloop transportation, etc. The main goal of the journal is to maintain high quality of publications, serving as a medium for railway academia and industry to exchange new ideas and share the latest achievements in scientific research, technical innovation and industrial development in railway science and engineering. The topics include but are not limited to Design theory and construction technology System dynamics and safetyElectrification, signaling and communicationOperation and maintenanceSystem health monitoring and reliability Environmental impact and sustainabilityCutting-edge technologiesThe publication costs for Railway Engineering Science are fully covered by Southwest Jiaotong University so authors do not need to pay any article-processing charges.