Development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Osamah Raheem, I. Aksenov, Yu. R. Redkin, A. Gorshkov, S. Sorokin, I. Atlasov, O. Kravets
{"title":"Development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements","authors":"Osamah Raheem, I. Aksenov, Yu. R. Redkin, A. Gorshkov, S. Sorokin, I. Atlasov, O. Kravets","doi":"10.59035/obhp8561","DOIUrl":null,"url":null,"abstract":"The article continues to review the approach to designing the architecture of a distributed information monitoring system and quality management of communication services provided by the infrastructures of the Internet of Things and the industrial Internet of Things, based on solutions that support machine-to-machine and human-machine interaction. The development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements is proposed. The matrix structure of the LSTM network memory cell is proposed, which takes into account the spatio-temporal correlation of load parameters associated with the time lag of its propagation and is a matrix of connectivity of LSTM network hyperparameters and accumulated values of load parameters of monitoring nodes in the vicinity of a controlled monitoring node, taking into account the characteristics of the time series of propagation of load in stationarity moments.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":"55 9","pages":""},"PeriodicalIF":16.4000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59035/obhp8561","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

The article continues to review the approach to designing the architecture of a distributed information monitoring system and quality management of communication services provided by the infrastructures of the Internet of Things and the industrial Internet of Things, based on solutions that support machine-to-machine and human-machine interaction. The development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements is proposed. The matrix structure of the LSTM network memory cell is proposed, which takes into account the spatio-temporal correlation of load parameters associated with the time lag of its propagation and is a matrix of connectivity of LSTM network hyperparameters and accumulated values of load parameters of monitoring nodes in the vicinity of a controlled monitoring node, taking into account the characteristics of the time series of propagation of load in stationarity moments.
基于具有长链短时记忆元素的递归神经网络,开发智能监控代理的神经网络模型
文章继续回顾了物联网和工业物联网基础设施提供的分布式信息监控系统和通信服务质量管理的架构设计方法,其基础是支持机器到机器和人机交互的解决方案。本文提出了基于具有长链短时记忆元素的递归神经网络的智能监控代理神经网络模型的开发方法。提出了 LSTM 网络存储单元的矩阵结构,该结构考虑了负载参数与其传播时滞相关的时空相关性,是 LSTM 网络超参数与受控监测节点附近监测节点负载参数累积值的连接矩阵,同时考虑了负载在静止时刻传播的时间序列特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
×
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