LSTM神经网络方法在时间序列建模中的研究

Г.Г. Рапаков, В.А. Горбунов, Сергей Владимирович Дианов, Л.В. Елизарова
{"title":"LSTM神经网络方法在时间序列建模中的研究","authors":"Г.Г. Рапаков, В.А. Горбунов, Сергей Владимирович Дианов, Л.В. Елизарова","doi":"10.23859/1994-0637-2023-3-114-4","DOIUrl":null,"url":null,"abstract":"В работе представлены результаты применения методов машинного обучения в задаче прогнозирования экономического временного ряда. На основе компьютерного моделирования разработана программная реализация LSTM-нейронной сети для товарной позиции из номенклатурного ряда за пятилетний период. Итоги исследования использованы при разработке корпоративной информационно-аналитической системы (ИАС).\n In this research, the authors present the results of the machine learning methods and algorithm application for development of LSTM neural network in order to time series modeling. Based on the application of artificial intelligence methods and five-year monitoring data a neural network software model for forecasting the time series of an economic indicator has been developed. The results were used in the corporate business intelligence system.","PeriodicalId":102323,"journal":{"name":"Cherepovets State University Bulletin","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research of the LSTM neural network approach in time series modeling\",\"authors\":\"Г.Г. Рапаков, В.А. Горбунов, Сергей Владимирович Дианов, Л.В. Елизарова\",\"doi\":\"10.23859/1994-0637-2023-3-114-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"В работе представлены результаты применения методов машинного обучения в задаче прогнозирования экономического временного ряда. На основе компьютерного моделирования разработана программная реализация LSTM-нейронной сети для товарной позиции из номенклатурного ряда за пятилетний период. Итоги исследования использованы при разработке корпоративной информационно-аналитической системы (ИАС).\\n In this research, the authors present the results of the machine learning methods and algorithm application for development of LSTM neural network in order to time series modeling. Based on the application of artificial intelligence methods and five-year monitoring data a neural network software model for forecasting the time series of an economic indicator has been developed. The results were used in the corporate business intelligence system.\",\"PeriodicalId\":102323,\"journal\":{\"name\":\"Cherepovets State University Bulletin\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cherepovets State University Bulletin\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23859/1994-0637-2023-3-114-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cherepovets State University Bulletin","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23859/1994-0637-2023-3-114-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Research of the LSTM neural network approach in time series modeling
В работе представлены результаты применения методов машинного обучения в задаче прогнозирования экономического временного ряда. На основе компьютерного моделирования разработана программная реализация LSTM-нейронной сети для товарной позиции из номенклатурного ряда за пятилетний период. Итоги исследования использованы при разработке корпоративной информационно-аналитической системы (ИАС). In this research, the authors present the results of the machine learning methods and algorithm application for development of LSTM neural network in order to time series modeling. Based on the application of artificial intelligence methods and five-year monitoring data a neural network software model for forecasting the time series of an economic indicator has been developed. The results were used in the corporate business intelligence system.
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
期刊最新文献
Poetics of Nina Dashevskaya's short stories (From the collection "Volchok's Stories") Propositional-semantic aspect of the word–formation niche description with the formant -ush/a in Russian vernacular dialects Citation verbs of speaking in Japanese blogs: a case study А model for the formation of a unified educational environment for students of pedagogical areas of training in a multidisciplinary university Formation of translation competencies among law students
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1