Multivariate statistics. Process systems engineering objectives: modeling, estimation, monitoring, control, optimization, and their relationship to data analytics. Feature extraction and dimension reduction, clustering, classification, regression. Nonlinear techniques and analysis of dynamic data. Applications of advanced data analytics in chemical process engineering.
Multivariate statistics. Process systems engineering objectives: modeling, estimation, monitoring, control, optimization, and their relationship to data analytics. Feature extraction and dimension reduction, clustering, classification, regression. Nonlinear techniques and analysis of dynamic data. Applications of advanced data analytics in chemical process engineering.
