Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey

Gopaluni, R. Bhushan, Tulsyan, Aditya, Chachuat, Benoit, Huang, Biao, Lee, Jong Min, Amjad, Faraz, Damarla, Seshu Kumar, Kim, Jong Woo, Lawrence, Nathan P.

arXiv.org Artificial Intelligence 

Over the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning tools on large-scale nonlinear monitoring and control problems. This article provides a survey of recent results with applications in the process industry.

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