BDDS:一种基于二进制数的高效数据筛选算法

Haowei Lin, Xiaolong Xu
{"title":"BDDS:一种基于二进制数的高效数据筛选算法","authors":"Haowei Lin, Xiaolong Xu","doi":"10.1109/CYBERC.2018.00096","DOIUrl":null,"url":null,"abstract":"In order to improve the efficiency and accuracy of data analysis, excellent data screening algorithms are needed in this era of big data. This paper proposes a binary-digit-based data screening algorithm (BDDS), utilizing the binary storage form of data in hardware and recording the data changes over a period of time with a binary-bit recorder, whose number of digits in the binary form is used to remove the influence of the medium-distance data from the current data, left shift of the binary form is used to reduce the influence of the data which are very close to the current data, and the decimal meaning is used to determine whether the data are valid data. Experiments have proved that the algorithm, as an auxiliary algorithm, can be better combined with the current mainstream data analysis algorithms to reduce the impact of marginal data, save additional storage space, and improve the accuracy and efficiency of subsequent data analysis.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"BDDS: An Efficient Data Screening Algorithm Based on Binary Digit\",\"authors\":\"Haowei Lin, Xiaolong Xu\",\"doi\":\"10.1109/CYBERC.2018.00096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the efficiency and accuracy of data analysis, excellent data screening algorithms are needed in this era of big data. This paper proposes a binary-digit-based data screening algorithm (BDDS), utilizing the binary storage form of data in hardware and recording the data changes over a period of time with a binary-bit recorder, whose number of digits in the binary form is used to remove the influence of the medium-distance data from the current data, left shift of the binary form is used to reduce the influence of the data which are very close to the current data, and the decimal meaning is used to determine whether the data are valid data. Experiments have proved that the algorithm, as an auxiliary algorithm, can be better combined with the current mainstream data analysis algorithms to reduce the impact of marginal data, save additional storage space, and improve the accuracy and efficiency of subsequent data analysis.\",\"PeriodicalId\":282903,\"journal\":{\"name\":\"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)\",\"volume\":\"145 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CYBERC.2018.00096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CYBERC.2018.00096","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

在这个大数据时代,为了提高数据分析的效率和准确性,需要优秀的数据筛选算法。提出了一种binary-digit-based数据筛选算法(bdd),利用二进制存储硬件和记录的形式的数据在一段时间内的数据变化与二进制位记录仪,其号码位数的二进制形式用于去除的影响中等距离的数据从当前数据左移的二进制形式是用来减少的影响数据非常接近当前的数据,并使用十进制含义来确定数据是否为有效数据。实验证明,该算法作为一种辅助算法,可以更好地与当前主流的数据分析算法相结合,减少边缘数据的影响,节省额外的存储空间,提高后续数据分析的准确性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
BDDS: An Efficient Data Screening Algorithm Based on Binary Digit
In order to improve the efficiency and accuracy of data analysis, excellent data screening algorithms are needed in this era of big data. This paper proposes a binary-digit-based data screening algorithm (BDDS), utilizing the binary storage form of data in hardware and recording the data changes over a period of time with a binary-bit recorder, whose number of digits in the binary form is used to remove the influence of the medium-distance data from the current data, left shift of the binary form is used to reduce the influence of the data which are very close to the current data, and the decimal meaning is used to determine whether the data are valid data. Experiments have proved that the algorithm, as an auxiliary algorithm, can be better combined with the current mainstream data analysis algorithms to reduce the impact of marginal data, save additional storage space, and improve the accuracy and efficiency of subsequent data analysis.
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
Information Fusion VIA Optimized KECA with Application to Audio Emotion Recognition Application Research of YOLO v2 Combined with Color Identification Decentralized Cross-Layer Optimization for Energy-Efficient Resource Allocation in HetNets A Smart QoE Aware Network Selection Solution for IoT Systems in HetNets Based 5G Scenarios Improving Word Representation with Word Pair Distributional Asymmetry
×
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