使用Apache Spark模块实现时间序列传感器数据评估的统计方法

Katalin Ferencz, J. Domokos, L. Kovács
{"title":"使用Apache Spark模块实现时间序列传感器数据评估的统计方法","authors":"Katalin Ferencz, J. Domokos, L. Kovács","doi":"10.1109/SACI55618.2022.9919485","DOIUrl":null,"url":null,"abstract":"The most important driving force in today's industry is fast and efficient data processing and evaluation. To this end, it is important for the industry to pay attention and resources to real-time analysis of the large amount of data collected, so that valuable information can be used to detect outliers in a timely manner, false data, or predictions to prevent unexpected costs. This data analysis requires the usage of a variety of algorithms appropriate to the purpose, with a very wide range of possibilities. To provide fast data analysis that can be used in the industry, in this paper we show how statistical analysis of time series data can be performed using the capabilities of the Apache Spark unified engine.","PeriodicalId":105691,"journal":{"name":"2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A statistical approach to time series sensor data evaluation using Apache Spark modules\",\"authors\":\"Katalin Ferencz, J. Domokos, L. Kovács\",\"doi\":\"10.1109/SACI55618.2022.9919485\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most important driving force in today's industry is fast and efficient data processing and evaluation. To this end, it is important for the industry to pay attention and resources to real-time analysis of the large amount of data collected, so that valuable information can be used to detect outliers in a timely manner, false data, or predictions to prevent unexpected costs. This data analysis requires the usage of a variety of algorithms appropriate to the purpose, with a very wide range of possibilities. To provide fast data analysis that can be used in the industry, in this paper we show how statistical analysis of time series data can be performed using the capabilities of the Apache Spark unified engine.\",\"PeriodicalId\":105691,\"journal\":{\"name\":\"2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI55618.2022.9919485\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI55618.2022.9919485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

当今行业最重要的驱动力是快速高效的数据处理和评估。为此,行业需要关注并投入资源对收集到的大量数据进行实时分析,以便利用有价值的信息及时发现异常值、虚假数据或预测,以防止意外成本的产生。这种数据分析需要使用各种适合目的的算法,具有非常广泛的可能性。为了提供可用于行业的快速数据分析,在本文中,我们展示了如何使用Apache Spark统一引擎的功能执行时间序列数据的统计分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A statistical approach to time series sensor data evaluation using Apache Spark modules
The most important driving force in today's industry is fast and efficient data processing and evaluation. To this end, it is important for the industry to pay attention and resources to real-time analysis of the large amount of data collected, so that valuable information can be used to detect outliers in a timely manner, false data, or predictions to prevent unexpected costs. This data analysis requires the usage of a variety of algorithms appropriate to the purpose, with a very wide range of possibilities. To provide fast data analysis that can be used in the industry, in this paper we show how statistical analysis of time series data can be performed using the capabilities of the Apache Spark unified engine.
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