比较发电对象的智能方法

M. Hasanov, A. Zakovorotniy, S. Leonov, G. Khrypunov, V. Dmitrienko, A. Klochko
{"title":"比较发电对象的智能方法","authors":"M. Hasanov, A. Zakovorotniy, S. Leonov, G. Khrypunov, V. Dmitrienko, A. Klochko","doi":"10.1109/IEPS51250.2020.9263211","DOIUrl":null,"url":null,"abstract":"A new method of synthesizing neural network for comparing, identifying, and classifying various objects through bipolar encoding of their attributes is offered. The mentioned method broadens the neuron network applicability sphere for solving tasks of identification and classification due to the use of proximity functions applying finer proximity attributes for discrete objects than the Hemming’s distance.","PeriodicalId":235261,"journal":{"name":"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Intellectual methods of comparing power generating objects\",\"authors\":\"M. Hasanov, A. Zakovorotniy, S. Leonov, G. Khrypunov, V. Dmitrienko, A. Klochko\",\"doi\":\"10.1109/IEPS51250.2020.9263211\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method of synthesizing neural network for comparing, identifying, and classifying various objects through bipolar encoding of their attributes is offered. The mentioned method broadens the neuron network applicability sphere for solving tasks of identification and classification due to the use of proximity functions applying finer proximity attributes for discrete objects than the Hemming’s distance.\",\"PeriodicalId\":235261,\"journal\":{\"name\":\"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEPS51250.2020.9263211\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEPS51250.2020.9263211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

提出了一种综合神经网络的方法,通过对物体属性进行双极编码,对物体进行比较、识别和分类。由于使用接近函数对离散对象应用比Hemming距离更精细的接近属性,该方法拓宽了神经元网络解决识别和分类任务的适用范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intellectual methods of comparing power generating objects
A new method of synthesizing neural network for comparing, identifying, and classifying various objects through bipolar encoding of their attributes is offered. The mentioned method broadens the neuron network applicability sphere for solving tasks of identification and classification due to the use of proximity functions applying finer proximity attributes for discrete objects than the Hemming’s distance.
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:481959085
Book学术官方微信