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Applying data mining in the context of Industrial Internet

By Oliviu Matei, Kevin Nagorny and Karsten Stoebener

Abstract

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

Topics: machine learning, data mining, k-nearest neigh-bour, neural network, support vector machine, rule induction, Electronic computers. Computer science, QA75.5-76.95, Instruments and machines, QA71-90, Mathematics, QA1-939, Science, Q
Publisher: The Science and Information (SAI) Organization
Year: 2016
OAI identifier: oai:doaj.org/article:e237432ee57741d9a562889ab1bd2185
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