###
计算机系统应用:2018,27(8):187-192
本文二维码信息
码上扫一扫!
基于标签技术和熵权法的缺陷推荐研究
齐敬先1, 刘翌2, 蒋宇2, 闫训超1, 杨剑1
(1.南瑞集团(国网电力科学研究院)有限公司, 南京 211000;2.国网江苏省电力有限公司, 南京 211000)
Research on Device Defect Recommendation Based on Tag Technology and Entropy Weight Method
QI Jing-Xian1, LIU Yi2, JIANG Yu2, YAN Xun-Chao1, YANG Jian1
(1.Nari Group Corporation(State Grid Electric Power Research Institute), Nanjing 211000, China;2.State Grid Jiangsu Electric Power Co. Ltd., Nanjing 211000, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 207次   下载 148
投稿时间:2017-12-05    修订日期:2017-12-27
中文摘要: 针对电力系统,设备(资产)运维管理系统(PMS)与调度管理系统(OMS)之间的设备缺陷互联需要PMS运维人员进行主观判断及手动选择操作,导致人员工作量大幅增加且数据交互的不合理程度和不完备程度也逐渐增大,本文提出了基于标签技术和熵权法的缺陷推荐方法.该方法首先以基于正向最大匹配算法、编辑距离和规则库的标签技术对缺陷数据进行标签化标识,然后采用熵权法对其标签进行评价,进而实现向调控员进行智能化推荐缺陷的目的.实验结果表明,通过该缺陷推荐方法的实施,显著减少了运维人员的缺陷选择工作量,并提升了缺陷信息推荐的准确性.
Abstract:According to the equipment defect interconnection between the Production Management System (PMS) and the Operation Management System (OMS) requires the PMS maintenance staff to choose the defects personally, resulting in staff workload increased significantly and the extent of unreasonable data interaction. At the same time, the incomplete degree of interconnection is gradually increased. The study proposes a recommendation defects method based on tag technology and entropy coefficient method. Firstly, the forward maximum matching algorithm and edit distance and rule database technologies are being used for tagging defects identification, and then using entropy weight method to evaluate the label, in order to achieve the intelligent recommendation to relevant personnel. The experimental results show that the implementation of the proposed method greatly reduces the workload of the relevant personnel, and improves the accuracy of the defect information recommendation.
文章编号:     中图分类号:    文献标志码:
基金项目:江苏省公司科技项目(J2017007)
引用文本:
齐敬先,刘翌,蒋宇,闫训超,杨剑.基于标签技术和熵权法的缺陷推荐研究.计算机系统应用,2018,27(8):187-192
QI Jing-Xian,LIU Yi,JIANG Yu,YAN Xun-Chao,YANG Jian.Research on Device Defect Recommendation Based on Tag Technology and Entropy Weight Method.COMPUTER SYSTEMS APPLICATIONS,2018,27(8):187-192

用微信扫一扫

用微信扫一扫