Applied Machine Learning in Chemical Process Engineering: A Practical Approach - Couverture souple

Couverture souple

ISBN 10 : 0443339430 ISBN 13 : 9780443339431

Editeur : Elsevier - Health Sciences Division, 2026

Synopsis

As machine learning capabilities and functionality increases, more industry experts and researchers are integrating applied machine learning into their research. Applied Machine Learning in Chemical Process Engineering: A Practical Approach serves as a comprehensive guide to equip the reader with the fundamental theory, practical guidance, methodologies, experimental design and troubleshooting knowledge needed to integrate machine learning into their processes. This book offers a comprehensive overview of all aspects of machine learning, from inception to integration that will allow readers from any scientific discipline to begin to examine the capabilities of machine learning. This book will then build upon this overview to offer worked examples and case studies, alongside practical methods-based guidance to walk the reader through integrating machine learning end-to-end. Finally, this book will offer critical discussion of concepts that are interwoven into the ever-evolving principles of machine learning such as ethics, safety and culpability that are crucial when working with machine learning. Applied Machine Learning in Chemical Process Engineering: A Practical Approach will be an invaluable resource for researchers, professionals in industry and academia, and students at graduate level and above who work in chemical engineering and are looking to automate, optimize or intensify their chemical processes. This book will also help professionals in other disciplines and industries looking into integrate machine learning into their work, such as though looking to scale up their processes to an industrial scale or conduct novel research.

A propos du livre

À propos des auteurs

Dr. Zafar Said is currently working as a Distinguished Associate Professor in the
Department of Mechanical and Aerospace Engineering at the United Arab Emirates
University, UAE. He received his doctoral degree in Mechanical Engineering from
the University of Malaya, Malaysia, and completed his postdoctoral research at
Khalifa University, UAE. Dr. Said is a recognized leader in energy technology,
nanofluids, and sustainable energy. His major areas of interest include heat
transfer, solar energy systems, and advanced thermofluids. His research focuses on
battery thermal management, enhancement of solar collectors using nanofluids
and turbulators, and the development of stable nanorefrigerants and
nanolubricants. He also applies artificial intelligence and machine learning to
predict thermophysical properties and optimize energy systems. He is the recipient
of several prestigious awards, including the Khalifa Award for Education as
Distinguished University Professor (2025), the Future Pioneer Award in
Sustainability (2025), and Best Academic Research at the 13th Dubai Award for
Sustainable Transport (2024). He has also received the Research and Innovation
Award from the UAE Ministry of Energy and Infrastructure (2022) and First Place in
Scientific Research at the Excellence and Creative Engineering Award (2023) by the
Society of Engineers, UAE. In recognition of his contributions, he has been
consistently ranked among the world's top 2% of scientists in the field of energy by
Elsevier BV and Stanford University. In addition to his academic duties, he actively
serves in editorial roles for several international journals and is a frequent keynote
speaker at global conferences.

Professor Muhammad Farooq is a distinguished academician currently serving as Professor and Head of the Department of Plant Sciences at Sultan Qaboos University in Muscat, Oman. He also holds concurrent positions as an Adjunct Professor at the University of Western Australia (since 2011) and a Distinguished Visiting Professor at Dankook University, South Korea (since 2013). His research, on crop water relations and adaptation to dryland environments, has encompassed providing fundamental understanding of the response of crops to abiotic stresses.

Détails de l'édition

• Éditeur: Elsevier - Health Sciences Division
• Date d'édition: 2026
• Langue: anglais
• ISBN 10: 0443339430
• ISBN 13: 9780443339431
• Reliure: Broché
• Nombre de pages: 350
• Éditeur: Said Zafar, Farooq Ph.D. Muhammad
• Coordonnées du fabricant: non disponible
• Personne responsable: Barbara Criscuolo; b.criscuolo@lswr.it; ; Via Spadolini, 7; Milano; 20141; Italie