Developed ABCLASS-Miner Classification Algorithm Based Rule Extraction for Denim Fabrics

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Gözde Katircioğlu, Emel Kizilkaya Aydoğan, Esra Akgul, Yılmaz Delice
{"title":"Developed ABCLASS-Miner Classification Algorithm Based Rule Extraction for Denim Fabrics","authors":"Gözde Katircioğlu, Emel Kizilkaya Aydoğan, Esra Akgul, Yılmaz Delice","doi":"10.35378/gujs.1185130","DOIUrl":null,"url":null,"abstract":"Obtaining and storing large amounts of data have become easier with the rapidly developing information technologies (IT). However, the data generated and collected, which are irrelevant in and of themselves, become useful only when they are analyzed for a specific reason. Data mining may transform raw data into useful information. In the present study, classification and analysis of denim fabric quality characteristics according to denim fabric production parameters were carried out. The present study proposes a new classification rule inference algorithm. The suggested approach is mostly based on Artificial Bee Colony Optimization (ABC), a swarm intelligence meta-heuristic. In each step of the algorithm, there are two phases called the employed bee phase and the onlooker bee phase. This algorithm has been compared with the classification algorithms in the related literature. This proposed algorithm is a new data mining tool that intelligently combines various metaheuristic and neural networks and can generate classification rules. The results indicate that the proposed data mining algorithms may be highly useful in determining weight and width in denim fabric manufacture.","PeriodicalId":12615,"journal":{"name":"gazi university journal of science","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"gazi university journal of science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35378/gujs.1185130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Obtaining and storing large amounts of data have become easier with the rapidly developing information technologies (IT). However, the data generated and collected, which are irrelevant in and of themselves, become useful only when they are analyzed for a specific reason. Data mining may transform raw data into useful information. In the present study, classification and analysis of denim fabric quality characteristics according to denim fabric production parameters were carried out. The present study proposes a new classification rule inference algorithm. The suggested approach is mostly based on Artificial Bee Colony Optimization (ABC), a swarm intelligence meta-heuristic. In each step of the algorithm, there are two phases called the employed bee phase and the onlooker bee phase. This algorithm has been compared with the classification algorithms in the related literature. This proposed algorithm is a new data mining tool that intelligently combines various metaheuristic and neural networks and can generate classification rules. The results indicate that the proposed data mining algorithms may be highly useful in determining weight and width in denim fabric manufacture.
开发了基于ABCLASS Miner分类算法的牛仔织物规则提取
随着信息技术的快速发展,获取和存储大量数据变得更加容易。然而,生成和收集的数据本身并不相关,只有在出于特定原因进行分析时才会有用。数据挖掘可以将原始数据转换为有用的信息。本研究根据牛仔布生产参数,对牛仔布的质量特征进行了分类分析。本研究提出了一种新的分类规则推理算法。所提出的方法主要基于人工蜂群优化(ABC),这是一种群体智能元启发式算法。在算法的每一步中,都有两个阶段,称为使用蜜蜂阶段和观察蜜蜂阶段。该算法已与相关文献中的分类算法进行了比较。该算法是一种新的数据挖掘工具,它智能地结合了各种元启发式和神经网络,可以生成分类规则。结果表明,所提出的数据挖掘算法在确定牛仔布生产中的重量和宽度方面可能非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
gazi university journal of science
gazi university journal of science MULTIDISCIPLINARY SCIENCES-
CiteScore
1.60
自引率
11.10%
发文量
87
期刊介绍: The scope of the “Gazi University Journal of Science” comprises such as original research on all aspects of basic science, engineering and technology. Original research results, scientific reviews and short communication notes in various fields of science and technology are considered for publication. The publication language of the journal is English. Manuscripts previously published in another journal are not accepted. Manuscripts with a suitable balance of practice and theory are preferred. A review article is expected to give in-depth information and satisfying evaluation of a specific scientific or technologic subject, supported with an extensive list of sources. Short communication notes prepared by researchers who would like to share the first outcomes of their on-going, original research work are welcome.
×
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