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水电站设备检修智能知识检索与推荐模型研究应用 被引量:1

Research and Application of Intelligent Knowledge Retrieval and Recommendation Model for Equipment Maintenance of Hydropower Stations
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摘要 为进一步提高标准化水电站设备检修作业效率,增强智慧企业标准化设备检修有效管理与知识传承能力,对标准化水电站设备检修智能平台技术需求进行分析,以搭建智能设备检修知识辅助平台为基础,设计了平台整体架构,提出了智能化关键技术解决方案,并完成了水电站设备检修中知识管理、检索技术和推荐技术等,克服了传统水电站设备检修中知识无法沉淀的问题。该技术方案已成功推广并应用于大岗山水电站标准化设备检修中,有效满足了水电设备检修管理需求并提高了生产效率,取得了较大的经济社会效益。 In order to further improve the efficiency of standardized equipment maintenance of hydropower stations and enhance the effective management and knowledge inheritance capabilities of intelligent enterprises in standardized equipment maintenance,the technical requirements on the intelligent platform of standardized equipment maintenance for hydropower stations is analyzed.Based on building an intelligent equipment maintenance knowledge assistance platform,the overall architecture of platform is designed,and the key intelligent technology solutions are proposed.The knowledge management,retrieval technology and recommendation technology in the equipment maintenance of hydropower stations are completed,which overcomes the problem that the knowledge cannot be accumulated in traditional equipment maintenance of hydropower stations.The proposed technical solution has been successfully promoted and applied to the standardized equipment maintenance of Dagangshan Hydropower Station,which effectively meets the needs of hydropower equipment maintenance management and production efficiency improvement,and achieve significant economic and social benefits.
作者 胡应春 徐正刚 王乐宁 张思洪 HU Yingchun;XU Zhenggang;WANG Yuening;ZHANG Sihong(CHN Energy Dadu River Hydropower Development Co.,Ltd.,Chengdu 610000,Sichuan,China)
出处 《水力发电》 CAS 2024年第2期78-84,共7页 Water Power
关键词 标准化 设备检修 知识管理 检索推荐 语义表示 注意力机制 standardization equipment maintenance knowledge management search recommendation semantic representation attention mechanism
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  • 1Alexander Hinneburg,Daniel A Keim.A General Approach to Clustering in Large Databases with Noise[J].Knowledge and Information Systems,2003(5):387-415.
  • 2XiaoGao Yu,XiaoPeng Yu.The Research on an adaptive k-nearest neighbors classifier[C]//ICMLC.2006:1241-1246.
  • 3Han Jiawei,Micheline Kamber.Data Mining-Concepts and Techniques[M].China Machine Press,Beijing,2004.
  • 4Xiaogao Yu,Xiaopeng Yu.An Adaptive Information Grid Architecture for Recommendation System[C]//APSCC'06.2006:560-565.
  • 5Zhaohui Tang,Jamie Maclennan,Peter Pyungchul Kim.Building Data Mining Solutions with OLE DB for DM and XML for Analysis[J].SIGMOD Record,2005,34(2):3-5.
  • 6Badrul Sarwar,George Karypis,Joseph Konstan.Item-based Collaborative Filtering Recommendation Algorithms[J].WWW10,2001,5:1-5.
  • 7Robin B.Hybrid recommender system.survey and experiments[J].User Modeling and User Adapted Interaction,2002,12(4):331-370.
  • 8Xiaogao Yu,Xiaopeng Yu.A Knowledge-Based Approach for Semantic Service Composition[C]//IMACS.2006:1814-1821.
  • 9Biggs,Maggie.E-business dynamics will lead savvy CTOs to intelligent business process integration[J].InfoWorld,2000,22(20):76.
  • 10关杰林,李天智.梯级水电站“调控一体化”管理模式的探索[J].水电站机电技术,2009,32(6):60-62. 被引量:8

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