基于机器学习算法的高效内存管理研究

Beom-Joo Park, Min-Soo Kang, Minho Lee, Y. Jung
{"title":"基于机器学习算法的高效内存管理研究","authors":"Beom-Joo Park, Min-Soo Kang, Minho Lee, Y. Jung","doi":"10.7236/IJASC.2017.6.1.39","DOIUrl":null,"url":null,"abstract":"As the industry grows, the amount of data grows exponentially, and data analysis using these serves as a predictable solution. As data size increases and processing speed increases, it has begun to be applied to new fields by combining artificial intelligence technology as well as simple big data analysis. In this paper, we propose a method to quickly apply a machine learning based algorithm through efficient resource allocation. The proposed algorithm allocates memory for each attribute. Learning Distinct of Attribute and allocating the right memory. In order to compare the performance of the proposed algorithm, we compared it with the existing K-means algorithm. As a result of measuring the execution time, the speed was improved.","PeriodicalId":297506,"journal":{"name":"The International Journal of Advanced Smart Convergence","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Study on Efficient Memory Management Using Machine Learning Algorithm\",\"authors\":\"Beom-Joo Park, Min-Soo Kang, Minho Lee, Y. Jung\",\"doi\":\"10.7236/IJASC.2017.6.1.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the industry grows, the amount of data grows exponentially, and data analysis using these serves as a predictable solution. As data size increases and processing speed increases, it has begun to be applied to new fields by combining artificial intelligence technology as well as simple big data analysis. In this paper, we propose a method to quickly apply a machine learning based algorithm through efficient resource allocation. The proposed algorithm allocates memory for each attribute. Learning Distinct of Attribute and allocating the right memory. In order to compare the performance of the proposed algorithm, we compared it with the existing K-means algorithm. As a result of measuring the execution time, the speed was improved.\",\"PeriodicalId\":297506,\"journal\":{\"name\":\"The International Journal of Advanced Smart Convergence\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The International Journal of Advanced Smart Convergence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7236/IJASC.2017.6.1.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Journal of Advanced Smart Convergence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7236/IJASC.2017.6.1.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

随着行业的发展,数据量呈指数级增长,使用这些数据进行数据分析是一种可预测的解决方案。随着数据量的增加和处理速度的提高,它已经开始结合人工智能技术和简单的大数据分析应用到新的领域。在本文中,我们提出了一种通过有效的资源分配快速应用基于机器学习的算法的方法。该算法为每个属性分配内存。学习属性的区别,分配正确的内存。为了比较所提出算法的性能,我们将其与现有的K-means算法进行了比较。由于测量了执行时间,速度得到了提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on Efficient Memory Management Using Machine Learning Algorithm
As the industry grows, the amount of data grows exponentially, and data analysis using these serves as a predictable solution. As data size increases and processing speed increases, it has begun to be applied to new fields by combining artificial intelligence technology as well as simple big data analysis. In this paper, we propose a method to quickly apply a machine learning based algorithm through efficient resource allocation. The proposed algorithm allocates memory for each attribute. Learning Distinct of Attribute and allocating the right memory. In order to compare the performance of the proposed algorithm, we compared it with the existing K-means algorithm. As a result of measuring the execution time, the speed was improved.
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