自动化仪表2024,Vol.45Issue(11) :96-100.DOI:10.16086/j.cnki.issn1000-0380.2023020105

基于GCNN推荐模型的智能工单自动化研判系统研究

Research on Automated Research and Judgment System for Intelligent Work Order Based on GCNN Recommendation Model

梁静 张建文 王辉 刘飞 候智圆
自动化仪表2024,Vol.45Issue(11) :96-100.DOI:10.16086/j.cnki.issn1000-0380.2023020105

基于GCNN推荐模型的智能工单自动化研判系统研究

Research on Automated Research and Judgment System for Intelligent Work Order Based on GCNN Recommendation Model

梁静 1张建文 1王辉 1刘飞 1候智圆1
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作者信息

  • 1. 国家电网山东省电力公司菏泽供电公司,山东 菏泽 274000
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摘要

为了提高数据信息的计算速度,设计了一种基于图卷积神经网络(GCNN)推荐模型的智能工单自动化研判系统.采用自动化监控与智能化处理技术,分析工单数据类型的相关情况.创造性地使用将人工智能和GCNN推荐模型相结合的方式,使工单自动化研判系统实现对工单的自动分类识别,以实现工单创建、智能分配、内部工单流转等.将5G通信技术应用到系统,加强对工单信息反馈的响应,以提高数据信息处理能力.试验结果表明,该系统的工单完成率在 90%以上、干扰率在 2%以下.该研究为智能工单类型自动化研判提供了可行方案.

Abstract

To improve the computational speed of data information,an intelligent work order automated research and judgment system based on graph convolutional neural network(GCNN)recommendation model is designed.Automated monitoring and intelligent processing techniques are used to analyze the situation related to work order data types.Creatively using the combination of artificial intelligence and GCNN recommendation model,the work order automation research and judgment system realizes the automatic classification and identification of work orders to realize work order creation,intelligent allocation,and internal work order flow,etc.5G communication technology is applied to the system to strengthen the response to work order information feedback and improve the data information processing capability.The test results show that the work order completion rate of the system is more than 90%,and the interference rate is under 2%.The research provides a feasible program for automated research and judgment of intelligent work order types.

关键词

电力监控自动化/图卷积神经网络/工单自动化/人工智能/研判系统/5G通信

Key words

Power monitoring automation/Graph convolutional neural network(GCNN)/Work order automation/Artificial intelligence/Research and judgment system/5G communication

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出版年

2024
自动化仪表
中国仪器仪表学会 上海工业自动化仪表研究院

自动化仪表

CSTPCD
影响因子:0.655
ISSN:1000-0380
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