文章基本信息

标题：Applying data mining in the context of Industrial Internet
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作者：Oliviu Matei ; Kevin Nagorny ; Karsten Stoebener 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：1
DOI：10.14569/IJACSA.2016.070184
出版社：Science and Information Society (SAI)
摘要：Nowadays, (industrial) companies invest more and more in connecting with their clients and machines deployed to the clients. Mining all collected data brings up several technical challenges, but doing it means getting a lot of insight useful for improving equipments. We define two approaches in mining the data in the context of Industrial Internet, applied to one of the leading companies in shoe production lines, but easily extendible to any producer. For each approach, various machine learning algorithms are applied along with a voting system. This leads to a robust model, easy to adapt for any machine.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; machine learning; data mining; k-nearest neigh-bour; neural network; support vector machine; rule induction