ICCSA Workshops最新文献

筛选
英文 中文
Prediction of Frequent Items to One Dimensional Stream Data 一维流数据频繁项的预测
ICCSA Workshops Pub Date : 2007-08-26 DOI: 10.1109/ICCSA.2007.61
D. Chai, B. Hwang, Eun Hee Kim, Long Jin, K. Ryu
{"title":"Prediction of Frequent Items to One Dimensional Stream Data","authors":"D. Chai, B. Hwang, Eun Hee Kim, Long Jin, K. Ryu","doi":"10.1109/ICCSA.2007.61","DOIUrl":"https://doi.org/10.1109/ICCSA.2007.61","url":null,"abstract":"Data mining in the stream data handles quality and data analysis using extremely large and infinite amount of data and disk or memory with limited volume. In such traditional transaction environment it is impossible to perform frequent items mining because it requires analyzing which item is a frequent one to continuously incoming stream data and which is probable to become a frequent item. This paper proposes a way to predict frequent items using regression model to the continuously incoming one dimensional stream data like the time series data. By establishing the regression model from the stream data, it may be used as a prediction model to uncertain items. The proposing way will exhibit its effectiveness through experiment in stream data.","PeriodicalId":285203,"journal":{"name":"ICCSA Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131456870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
IFS Matlab Generator: A Computer Tool for Displaying IFS Fractals IFS Matlab生成器:显示IFS分形的计算机工具
ICCSA Workshops Pub Date : 1900-01-01 DOI: 10.1109/ICCSA.2009.10
A. Gálvez
{"title":"IFS Matlab Generator: A Computer Tool for Displaying IFS Fractals","authors":"A. Gálvez","doi":"10.1109/ICCSA.2009.10","DOIUrl":"https://doi.org/10.1109/ICCSA.2009.10","url":null,"abstract":"Fractals are among the most exciting and intriguing mathematical objects ever discovered. A particular type of fractals, the Iterated Function Systems (IFS), has received a lot of attention due to its appealing combination of conceptual simplicity, computational efficiency and great ability to reproduce natural formations and complex phenomena. This paper introduces a new Matlab program, called \"IFS Matlab Generator\", for generating and rendering IFS fractals. In addition to providing a gentle introduction to the mathematical basis of IFS, two of the most important rendering algorithms, the deterministic algorithm and the probabilistic algorithm (also called \"chaos game\" algorithm), are briefly outlined. A critical point of chaos game is the choice of the set of probabilities associated with the iterated functions. This issue will be briefly discussed in this paper: we analyze the efficiency of the chaos game algorithm, comparing the standard method for choosing the probabilities proposed by Michael Barnsley with another method based on a new multifractal technique. The latter method optimizes the rendering process by obtaining the most efficient set of probabilities. Some examples aimed at illustrating this technique along with a gallery of beautiful two-dimensional fractal objects are also given.","PeriodicalId":285203,"journal":{"name":"ICCSA Workshops","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131088530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
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×
相关产品
×
本文献相关产品
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:604180095
Book学术官方微信