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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Applying data mining in the context of Industrial Internet

Author 1: Oliviu Matei Author 2: Kevin Nagorny Author 3: Karsten Stoebener
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 1 · Published 2016 · Cited by 10

DOI: https://doi.org/10.14569/IJACSA.2016.070184

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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.

Keywords

machine learning data mining k-nearest neigh-bour neural network support vector machine rule induction

How to Cite this Article

Matei, O., Nagorny, K., & Stoebener, K. (2016). Applying data mining in the context of Industrial Internet. International Journal of Advanced Computer Science and Applications, 7(1). https://doi.org/10.14569/IJACSA.2016.070184

Matei, Oliviu, et al.. "Applying data mining in the context of Industrial Internet." International Journal of Advanced Computer Science and Applications, vol. 7, no. 1, 2016, https://doi.org/10.14569/IJACSA.2016.070184.

@article{Matei2016,
  title     = {Applying data mining in the context of Industrial Internet},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {1},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Oliviu Matei and Kevin Nagorny and Karsten Stoebener},
  doi       = {10.14569/IJACSA.2016.070184},
  url       = {https://doi.org/10.14569/IJACSA.2016.070184}
}

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