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基于知识关联的典型业务场景数字标准智能化应用研究

Research on Intelligent Application of Digital Standards in Typical Business Scenarios Based on Knowledge Association
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摘要 在国家战略、能源革命、技术革新和数字化生存的多重浪潮中,电网企业作为能源行业的核心枢纽,实施数字化转型已经成为必然趋势。本文围绕基于场景的数字标准应用模式展开讨论,首先分析了基于场景的标准化通用理论模式,探讨如何将场景单元需求与标准条款知识内容进行关联,以便更好地应用标准,为数字标准的应用提供路径。然后,结合数字标准的特点,通过分析构建数字标准应用的总体思路和应用逻辑,厘清了基于场景的数字标准应用模式的内在关系。最后,以运维检修模块为例,分析基于知识关联的典型业务场景数字标准智能化应用的可行性和有效性,为持续深挖业务应用场景需求,充分释放标准价值提供参考意义。 Amidst the multiple waves of national strategy,energy revolution,technological innovation,and digital existence,the digital transformation of power grid enterprises,as the core hub of the energy industry,has become an inevitable trend.This paper discusses the application mode of digital standards based on scenarios.It starts by analyzing the general theoretical model of standardization based on scenarios and explores how to associate scenario unit needs with standard clause knowledge content to better apply standards,providing a pathway for the application of digital standards.Subsequently,combining the characteristics of digital standards,the paper analyzes the overall thinking and application logic of building digital standard applications,clarifying the internal relations of the digital standard application model based on scenarios.Finally,using the operation and maintenance inspection module as an example,the feasibility and effectiveness of the intelligent application of digital standards in typical business scenarios based on knowledge association are analyzed.This provides reference significance for continuously delving into business application scenario needs and fully unleashing the value of standards.
作者 范强 黄军凯 吕黔苏 李长兴 陈佳胜 林正平 FAN Qiang;HUANG Junkai;LYU Qiansu;LI Changxing;CHEN Jiasheng;LIN Zhengping(Electric Power Research Institute,Guizhou Power Grid Co.,Ltd.,Guiyang 550002, Guizhou, China;CSG Electric Power Research Institute, Guang zhou 510663, Guangdong, China)
出处 《电力大数据》 2023年第9期60-66,共7页 Power Systems and Big Data
基金 中国南方电网公司科技项目(066600KK52210002)。
关键词 数字标准 场景识别 标准结构化 知识关联 知识抽取 digital standards scene recognition standard structure knowledge association knowledge extraction
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