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。
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(Al)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 Al 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 objectivessafety,efficiency,economy,and serviceproposes 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.
作者
邱实
葛含章
卢睿
王卫东
王劲
魏炜
Shi Qiu;Hanzhang Ge;Rui Lu;Weidong Wang;Jin Wang;Wei Wei(Guangxi Transport Vocational and Technical College;Central South University;MOE Key Laboratory of Engineening Stuctures of Heavy Haul Railway;Center for Railway Infrastructure Smart Monitoring and Management;Center for Infrastructure Three-dimensional Digital Twin Engineering;CREC Cloudnet Information Technology Co.Ltd)
出处
《计算》
2025年第6期56-67,共12页
Computing Magazine of the CCF
基金
国家自然科学基金面上项目(52178442)。
关键词
高速铁路
复杂系统
人工智能
机器学习
全生命周期
文献综述
high-speed railway
complex system
artificial intelligence
machine learning
lifecycle
literature review
