人工神经网络在电能接收器无创识别中的应用

T. Kwater, J. Bartman
{"title":"人工神经网络在电能接收器无创识别中的应用","authors":"T. Kwater, J. Bartman","doi":"10.1109/PAEE.2017.8008982","DOIUrl":null,"url":null,"abstract":"This article concern to systems that support the manage economical use of electricity. An advisory and monitoring system equipped with artificial intelligence for non-invasive on-line identification of electrical devices was proposed. Research has been done on the basic element of the system, which is the classifier module. As data describing the objects, the electrical quantities obtained from the Elspec BlackBox 4500 analyzer were used. It implements the various configurations of artificial neural networks (ANN), to provide identification efficiency of 68%–91%. The advantages of the various classifiers due to their architecture ware pointed out.","PeriodicalId":397235,"journal":{"name":"2017 Progress in Applied Electrical Engineering (PAEE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Application of artificial neural networks in non-invasive identification of electric energy receivers\",\"authors\":\"T. Kwater, J. Bartman\",\"doi\":\"10.1109/PAEE.2017.8008982\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article concern to systems that support the manage economical use of electricity. An advisory and monitoring system equipped with artificial intelligence for non-invasive on-line identification of electrical devices was proposed. Research has been done on the basic element of the system, which is the classifier module. As data describing the objects, the electrical quantities obtained from the Elspec BlackBox 4500 analyzer were used. It implements the various configurations of artificial neural networks (ANN), to provide identification efficiency of 68%–91%. The advantages of the various classifiers due to their architecture ware pointed out.\",\"PeriodicalId\":397235,\"journal\":{\"name\":\"2017 Progress in Applied Electrical Engineering (PAEE)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Progress in Applied Electrical Engineering (PAEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PAEE.2017.8008982\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Progress in Applied Electrical Engineering (PAEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PAEE.2017.8008982","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

本文讨论的是支持管理节电的系统。提出了一种用于电气设备无创在线识别的人工智能咨询与监测系统。对系统的基本组成部分分类器模块进行了研究。作为描述物体的数据,使用Elspec BlackBox 4500分析仪获得的电量。它实现了人工神经网络(ANN)的各种配置,提供68%-91%的识别效率。指出了各种分类器在体系结构上的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of artificial neural networks in non-invasive identification of electric energy receivers
This article concern to systems that support the manage economical use of electricity. An advisory and monitoring system equipped with artificial intelligence for non-invasive on-line identification of electrical devices was proposed. Research has been done on the basic element of the system, which is the classifier module. As data describing the objects, the electrical quantities obtained from the Elspec BlackBox 4500 analyzer were used. It implements the various configurations of artificial neural networks (ANN), to provide identification efficiency of 68%–91%. The advantages of the various classifiers due to their architecture ware pointed out.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信