Robust operating performance assessment of flotation processes using convolutional neural networks and feature learning.

Application of Robust Model Predictive Control Using Principal Component Analysis to an Industrial Thickener.

Stable predictive control of continuous stirred-tank reactors using deep learning.

Sample-efficient reinforcement learning with knowledge-embedded hybrid model for optimal control of mining industry.

Safe reinforcement learning for industrial optimal control: A case study from metallurgical industry.

Collaborative Optimization Framework for the Industrial Thickening-Dewatering Process Based on Mixed Integer Linear Programming.

A general data-driven nonlinear robust optimization framework based on statistic limit and principal component analysis.

A process transfer model-based optimal compensation control strategy for batch process using just-in-time learning and trust region method.

Transfer learning for end-product quality prediction of batch processes using domain-adaption joint-Y PLS.

Ensemble regularized local finite impulse response models and soft sensor application in nonlinear dynamic industrial processes.

Gold Recovery Modeling Based on Interval Prediction for a Gold Cyanidation Leaching Plant.

Rapid Modeling Method for Performance Prediction of Centrifugal Compressor Based on Model Migration and SVM.

Real-time product quality control for batch processes based on stacked least-squares support vector regression models.