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Big-Data for Process Applications

He, Q. P., Auburn University
Yenkie, K., Rowan University

Real-world data can be a valuable asset for improving process design or operations. However, collecting and analyzing this data can be challenging due to data sparsity, heterogeneity, uncertainty, or dimensionality. This session seeks papers on the topic of data analysis and information management. Submissions from industry or collaborations between academia and industry are highly encouraged. Topics can cover both methods for data-analysis and information management, as well as applications.



Paper abstracts are public but to access Extended Abstracts, you must first purchase the conference proceedings.


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AIChE Undergraduate Student Members Free
Non-Members $225.00