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人工智能赋能高铁复杂系统管理:研究进展及未来展望

Artificial Intelligence Empowered Management of High-Speed Railway Complex Systems: Research Progress and Future Perspectives

  • 摘要: 高速铁路作为多技术子系统强耦合、跨生命周期动态演化的网络化复杂系统,其运行过程呈现高度非线性、多尺度与多主体协同特征,为管理工作带来极大挑战。近年来,人工智能(artificial intelligence, AI)的发展为高铁系统管理的智能化转型提供了技术支撑,如何将AI融合应用至各业务场景中成为研究热点。本文基于复杂性理论,系统性综述了AI技术在高铁全生命周期各阶段中的核心方法与应用进展,归纳了当前面临的数据治理、数模协同、接口割裂与知识嵌入等关键挑战,并围绕安全、效能、经济、服务四大核心目标,提出面向全生命周期数据融合与跨系统协同的未来发展方向,旨在为智能高铁2.0架构下的AI融合应用提供新思路。

     

    Abstract: High-speed railways, as networked complex systems characterized by strong coupling among multiple technological subsystems and dynamic evolution across the entire lifecycle, exhibit pronounced nonlinearity, multi-scale interactions, and multi-agent coordination during operation, posing substantial challenges to management. In recent years, the rapid development of artificial intelligence (AI) has provided crucial technical support for the intelligent transformation of high-speed railway management, and how to integrate AI into diverse business scenarios has become a key research focus. Building on complex systems theory, this article provides a systematic review of core AI methodologies and their application progress in the full-lifecycle management of high-speed railways, summarizes critical challenges including data governance, model–mechanism integration, interface fragmentation, and knowledge embedding, and, guided by four overarching objectives—safety, efficiency, economy, and service—proposes future directions for lifecycle-wide data fusion and cross-system intelligent collaboration. The findings aim to offer new insights into AI integration under the Intelligent High-Speed Railway 2.0 framework and to support the construction of a safer, more efficient, and sustainable intelligent railway management system.

     

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