Applications of Artificial Intelligence in Process Systems Engineering

<p>Part I: Introduction of AI and Big Data Analytics<br>1. Artificial Intelligence in Chemical Engineering: Past, Current, and Prospect.<br>2. Big Data Analytics in Process System Engineering<br>3. Advanced Computational Tools and Platform for Artificial Intelligence</p> <p>Part II: Property Prediction<br>4. Applications of Artificial Neural Networks for Thermodynamics: Vapor-Liquid Equilibrium Predictions<br>5. Support Vector Machines for The Prediction of Physical-Chemical Properties<br>6. Thermodynamics Prediction: Neural Networks Based Quantitative Structure Property Relationships<br>7. Intelligent Approaches to Forecast the Chemical Property: Case Study in Papermaking Process</p> <p>Part III: Process Modelling<br>8. Artificial Neural Networks for Modelling of Wastewater Treatment Process<br>9. COD Forecasting Based LSTM Algorithm for Wastewater Treatment Process<br>10. Comparisons of Deep Learning Methods for Process Modelling: A Case Study of Bio-Hydrogen Production<br>11. Deep Learning Based Energy Consumption Forecasting Model for Process Industry<br>12. Chemical Green Product Design Assisted with Machine Learning: Theory and Methods</p> <p>Part IV: Process Control and Fault Diagnosis<br>13. Artificial Intelligence for the Modelling and Control of Chemical Process Systems<br>14. Artificial Intelligence for Management and Control of The Pollution Minimization<br>15. Neural Network Based Framework for Fault Diagnosis<br>16. Application of Artificial Intelligence in Process Fault Diagnosis</p> <p>Part V: Process Optimization<br>17. Bi-Level Model Reduction for Multiscale Stochastic Optimization of Cooling Water System<br>18. Artificial Intelligence Algorithm Based Multi-Object Optimization of Flexible Flow Shop Smart Scheduling<br>19. Electricity Scheduling Optimization Model for Flexible Production Process<br>20. Data‐driven multistage adaptive robust optimization framework for planning and scheduling under uncertainty</p>