通信网络作为支撑数智经济发展的关键基础设施,网络业务需求日益增长、网络基础设施规模不断扩大、技术架构持续更新迭代,传统运维管理模式难以满足需求。本研究旨在构建行业软件定义运维平台,通过运维活动端到端的闭环管理和运维要素智能化驱动,实现业务场景的端到端自动化、智能化运维能力。通过机器学习、神经网络、知识图谱等算法及手段发现补充运维经验,管理各种运维要素、优化运维流程,帮助客户解决快速实现网络规划、建设、维护、运营和优化,帮助客户大幅降本增效,为广大政企客户的网络运维提供强有力的技术支持。本文详细探讨平台在提升自智网络等级、运维效率和降低成本方面的作用,为相关领域的研究和应用提供参考。The communication network, as a key infrastructure supporting the digital economy, has seen an increasing demand for network services and an expanding network infrastructure scale, as well as continuous updates to the technical architecture. The traditional operational and maintenance (O&M) model is no longer sufficient to meet the growing needs. This study aims to build a software-defined O&M platform for the industry, which aims to achieve end-to-end automated and intelligent operation and maintenance capabilities through closed-loop management of O&M activities and intelligent driving of O&M elements. By using machine learning, neural networks, knowledge graphs, and other algorithms and means, the platform can discover and supplement O&M experience, manage various O&M elements, optimize O&M processes, and help customers quickly achieve network planning, construction, maintenance, operation, and optimization. It can also help customers significantly reduce costs and increase efficiency, providing strong technical support for the network operation and maintenance of government and enterprise customers. This paper discusses in detail the role of the platform in enhancing self-intelligent network levels, operational efficiency, and reducing costs, providing reference for related research and applications.
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