Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering

Ren, Jingzheng
Shen, Weifeng
Man, Yi
DOng, Lichun

149,76 €(IVA inc.)

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithmsDiscusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosisGives direction to future development trends of AI technologies in chemical and process engineering INDICE: Part I: Introduction of AI and Big Data Analytics 1. Artificial Intelligence in Chemical Engineering: Past, Current, and Prospect. 2. Big Data Analytics in Process System Engineering 3. Advanced Computational Tools and Platform for Artificial Intelligence Part II: Property Prediction 4. Applications of Artificial Neural Networks for Thermodynamics: Vapor-Liquid Equilibrium Predictions 5. Support Vector Machines for The Prediction of Physical-Chemical Properties 6. Thermodynamics Prediction: Neural Networks Based Quantitative Structure Property Relationships 7. Intelligent Approaches to Forecast the Chemical Property: Case Study in Papermaking Process Part III: Process Modelling 8. Artificial Neural Networks for Modelling of Wastewater Treatment Process 9. COD Forecasting Based LSTM Algorithm for Wastewater Treatment Process 10. Comparisons of Deep Learning Methods for Process Modelling: A Case Study of Bio-Hydrogen Production 11. Deep Learning Based Energy Consumption Forecasting Model for Process Industry 12. Chemical Green Product Design Assisted with Machine Learning: Theory and Methods Part IV: Process Control and Fault Diagnosis 13. Artificial Intelligence for the Modelling and Control of Chemical Process Systems 14. Artificial Intelligence for Management and Control of The Pollution Minimization 15. Neural Network Based Framework for Fault Diagnosis 16. Application of Artificial Intelligence in Process Fault Diagnosis Part V: Process Optimization 17. Bi-Level Model Reduction for Multiscale Stochastic Optimization of Cooling Water System 18. Artificial Intelligence Algorithm Based Multi-Object Optimization of Flexible Flow Shop Smart Scheduling 19. Electricity Scheduling Optimization Model for Flexible Production Process 20. Data-driven?multistage adaptive robust?optimization?framework for planning and scheduling under uncertainty

  • ISBN: 978-0-12-821092-5
  • Editorial: Elsevier
  • Encuadernacion: Rústica
  • Páginas: 312
  • Fecha Publicación: 01/07/2021
  • Nº Volúmenes: 1
  • Idioma: Inglés