Cover for Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering

Book2021

Edited by:

Jingzheng Ren, Weifeng Shen, ... Lichun Dong

Applications of Artificial Intelligence in Process Systems Engineering

Book2021

 

Cover for Applications of Artificial Intelligence in Process Systems Engineering

Edited by:

Jingzheng Ren, Weifeng Shen, ... Lichun Dong

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Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applicatio ... read full description

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  2. Book chapterAbstract only

    Chapter 1 - Artificial intelligence in process systems engineering

    Tao Shi, Ao Yang, ... Yi Man

    Pages 1-10

  3. Book chapterAbstract only

    Chapter 2 - Deep learning in QSPR modeling for the prediction of critical properties

    Yang Su and Weifeng Shen

    Pages 11-37

  4. Book chapterAbstract only

    Chapter 3 - Predictive deep learning models for environmental properties

    Zihao Wang and Weifeng Shen

    Pages 39-66

  5. Book chapterAbstract only

    Chapter 4 - Automated extraction of molecular features in machine learning-based environmental property prediction

    Zihao Wang and Weifeng Shen

    Pages 67-92

  6. Book chapterAbstract only

    Chapter 5 - Intelligent approaches to forecast the chemical property: Case study in papermaking process

    Yang Zhang, Jigeng Li, ... Yi Man

    Pages 93-118

  7. Book chapterAbstract only

    Chapter 6 - Machine learning-based energy consumption forecasting model for process industry—Hybrid PSO-LSSVM algorithm electricity consumption forecasting model for papermaking process

    Yi Man, Yusha Hu, ... Mengna Hong

    Pages 119-142

  8. Book chapterAbstract only

    Chapter 7 - Artificial intelligence algorithm application in wastewater treatment plants: Case study for COD load prediction

    Zifei Wang and Yi Man

    Pages 143-164

  9. Book chapterAbstract only

    Chapter 8 - Application of machine learning algorithms to predict the performance of coal gasification process

    Zeynep Ceylan and Selim Ceylan

    Pages 165-186

  10. Book chapterAbstract only

    Chapter 9 - Artificial neural network and its applications: Unraveling the efficiency for hydrogen production

    Sushreeta Paul, Vijay Kumar and Priyanka Jha

    Pages 187-206

  11. Book chapterAbstract only

    Chapter 10 - Fault diagnosis in industrial processes based on predictive and descriptive machine learning methods

    Ahmed Ragab, Mohamed El Koujok, ... Mouloud Amazouz

    Pages 207-254

  12. Book chapterAbstract only

    Chapter 11 - Application of artificial intelligence in modeling, control, and fault diagnosis

    Mohsen Hadian, Seyed Mohammad Ebrahimi Saryazdi, ... Masoud Babaei

    Pages 255-323

  13. Book chapterAbstract only

    Chapter 12 - Integrated machine learning framework for computer-aided chemical product design

    Qilei Liu, Haitao Mao, ... Jian Du

    Pages 325-359

  14. Book chapterAbstract only

    Chapter 13 - Machine learning methods in drug delivery

    Rania M. Hathout

    Pages 361-380

  15. Book chapterAbstract only

    Chapter 14 - On the robust and stable flowshop scheduling under stochastic and dynamic disruptions

    Zhaolong Yang, Fuqiang Li and Feng Liu

    Pages 381-416

  16. Book chapterAbstract only

    Chapter 15 - Bi-level model reductions for multiscale stochastic optimization of cooling water system

    Qiping Zhu and Chang He

    Pages 417-445

  17. Book chapterAbstract only

    Chapter 16 - Artificial intelligence algorithm-based multi-objective optimization model of flexible flow shop smart scheduling

    Huanhuan Zhang, Jigeng Li, ... Yi Man

    Pages 447-472

  18. Book chapterAbstract only

    Chapter 17 - Machine learning-based intermittent equipment scheduling model for flexible production process

    Zifei Wang and Yi Man

    Pages 473-495

  19. Book chapterAbstract only

    Chapter 18 - Artificial intelligence algorithms for proactive dynamic vehicle routing problem

    Xianlong Ge and Yuanzhi Jin

    Pages 497-522

About the book

Description

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.

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.

Key Features

  • Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms
  • Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis
  • Gives direction to future development trends of AI technologies in chemical and process engineering
  • Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms
  • Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis
  • Gives direction to future development trends of AI technologies in chemical and process engineering

Details

ISBN

978-0-12-821092-5

Language

English

Published

2021

Copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

Imprint

Elsevier

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Editors

Jingzheng Ren

Assistant Professor, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China

Weifeng Shen

School of Chemistry and Chemical Engineering, Chongqing University, Chongqing, China

Yi Man

State Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou, China

Lichun Dong

School of Chemistry and Chemical Engineering, Chongqing University, Chongqing, China