The Innovation and Transfer of Computer Science and Technology in Recent and Modern Railway Transportation

This article aims to discuss the influence of computer technology on the innovation and technology transfer of modern railway transportation. By historical analysis and empirical research, this article first reviews the evolution of railway transportation from steam locomotive to High-Speed Railways, and then compares and analyzes the performance of the improved multi-objective particle swarm optimization (MPSO) algorithm and traditional particle swarm optimization (PSO) algorithm in train operation scheduling through designing simulation experiments. The experiment selected the representative train operation data sets, and the first 25 and 15 data items are used as training sets respectively to predict the subsequent data items, and the prediction results of MPSO algorithm, traditional PSO algorithm and support vector machine algorithm are compared. The results show that MPSO algorithm is excellent in prediction accuracy, convergence speed and error control, and its prediction results are closer to the actual train running state, which verifies the effectiveness of computer technology in optimizing railway transportation scheduling.

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Publication Details

Journal
International Journal of Intelligent Information Technologies
Published
2024-12-28
DOI
https://doi.org/10.4018/ijiit.365346
Primary Topic
Railway Systems and Energy Efficiency
Type
article
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article

The Innovation and Transfer of Computer Science and Technology in Recent and Modern Railway Transportation

Yuhan Ye, Hui Zhang
International Journal of Intelligent Information Technologies
Railway Systems and Energy Efficiency
article

The Innovation and Transfer of Computer Science and Technology in Recent and Modern Railway Transportation

Yuhan Ye, Hui Zhang
article en

Abstract

This article aims to discuss the influence of computer technology on the innovation and technology transfer of modern railway transportation. By historical analysis and empirical research, this article first reviews the evolution of railway transportation from steam locomotive to High-Speed Railways, and then compares and analyzes the performance of the improved multi-objective particle swarm optimization (MPSO) algorithm and traditional particle swarm optimization (PSO) algorithm in train operation scheduling through designing simulation experiments. The experiment selected the representative train operation data sets, and the first 25 and 15 data items are used as training sets respectively to predict the subsequent data items, and the prediction results of MPSO algorithm, traditional PSO algorithm and support vector machine algorithm are compared. The results show that MPSO algorithm is excellent in prediction accuracy, convergence speed and error control, and its prediction results are closer to the actual train running state, which verifies the effectiveness of computer technology in optimizing railway transportation scheduling.

International Journal of Intelligent Information TechnologiesVol. 21(1)
Wuhu Institute of Technology (CN), Sanming University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 64%
Railway Systems and Energy Efficiency
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The Innovation and Transfer of Computer Science and Technology in Recent and Modern Railway Transportation — Yuhan Ye, Hui Zhang · International Journal of Intelligent Information Technologies (2024) | TGRS Research Map | TGRS