IEEE Access (Jan 2017)

Data Mining and Analytics in the Process Industry: The Role of Machine Learning

  • Zhiqiang Ge,
  • Zhihuan Song,
  • Steven X. Ding,
  • Biao Huang

DOI
https://doi.org/10.1109/ACCESS.2017.2756872
Journal volume & issue
Vol. 5
pp. 20590 – 20616

Abstract

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Data mining and analytics have played an important role in knowledge discovery and decision making/supports in the process industry over the past several decades. As a computational engine to data mining and analytics, machine learning serves as basic tools for information extraction, data pattern recognition and predictions. From the perspective of machine learning, this paper provides a review on existing data mining and analytics applications in the process industry over the past several decades. The state-of-the-art of data mining and analytics are reviewed through eight unsupervised learning and ten supervised learning algorithms, as well as the application status of semi-supervised learning algorithms. Several perspectives are highlighted and discussed for future researches on data mining and analytics in the process industry.

Keywords