Computational Automation for Water Security: Enhancing Water Quality Management - Softcover

Softcover

ISBN 10: 0443333211 ISBN 13: 9780443333217

Verlag: Elsevier, 2025

Inhaltsangabe

Computational Automation for Water Security: Enhancing Water Quality Management is a comprehensive and insightful guide which explores the challenges posed by inefficient and outdated practices, presenting innovative solutions to enhance decision-making, optimizing water treatment processes, and ultimately improving environmental outcomes. Through the coverage of advanced computational techniques, such as data analysis, machine learning, and optimization strategies, readers will gain a deep understanding of how computational automation can revolutionize decision-making. This book is an invaluable resource for professionals, researchers, and policymakers seeking to stay at the forefront of water quality management practices, harnessing the power of computational automation for a cleaner, healthier future.

Über diesen Titel

Über die Autorinnen und Autoren

Ashutosh Kumar Dubey is an Associate Professor in the Department of Computer Science and Engineering at Chitkara University, Himachal Pradesh, India. He is also a Postdoctoral Fellow of the Ingenium Research Group Lab, Universidad
de Castilla-La Mancha, Ciudad Real, Spain.

Dr. Arun Lal Srivastav is an Associate Professor in the Department of Applied Sciences at Chitkara University, Himachal Pradesh, India.

Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science and Engineering at Chandigarh University, Punjab, India. He holds a Ph.D. in Computer Science from the University of Madras and is currently a Post-Doctoral Fellow with the Ingenium Research Group, Universidad de Castilla-La Mancha, Ciudad Real, Spain. He received his M.Tech in Computer Science and Engineering and B.Tech in Information Technology from Rajasthan Technical University, Kota, India. He has over thirteen years of academic teaching experience. His research interests include artificial intelligence, computer vision, image processing, data mining, machine learning, and renewable energy systems. He has authored and edited several books with leading international publishers and serves as a reviewer for reputed journals.

Fausto Pedro García Márquez works as a Professor and as Director of the Ingenium Research Group at the Universidad De Castilla-La Mancha, Spain. He is an Honorary Senior Research Fellow at Birmingham University, UK, and a Lecturer at the Postgraduate European Institute. He has published more than 150 papers and 31 books (Elsevier, Springer, Pearson, McGraw-Hill, Intech, IGI, Marcombo, AlfaOmega). He has been Principal Investigator in 4 European projects, 6 national projects, and more than 150 projects for universities, companies, and other institutions. His main interests are: Artificial Intelligence, Maintenance, Management, Renewable Energy, Transport, Advanced Analytics, and Data Science.

Dr. Dimitrios Giannakoudakis graduated as chemist from Aristotle University of Thessaloniki (AUTh) in Greece, where he obtained also two M.Sc. degrees (in Physical-chemistry & Electrochemistry and in New Educational Technologies). He received his PhD degree on “Nanotechnology and Materials Chemistry” from the City University of New York (CUNY) with full scholarship, in 02/2017. Then, he continued as postdoctoral-fellow and adjunct tutor at the City College of New York, AUTh, and the Institute of Physical Chemistry (IChF) of Polish Academy of Sciences. Afterwards, he served at IChF as adj. Assistant Professor and tutor of “Modern nano-Topics in Physical Chemistry”. Currently, he is Research Associate and tutor at AUTh.
He has co-authored more than 105 publications in leading peer-reviewed journals (avg. Impact Factor as 1st author above 11), with the articles to be cited more than 3000 times, one monograph by Springer, three edited books by Elsevier, more than 20 book chapters, and 3 invention patents.
For more details: www.DaGchem.com

Von der hinteren Coverseite

Computational Automation for Water Security: Enhancing Water Quality Management is a comprehensive and insightful guide which explores the challenges posed by inefficient and outdated practices, presenting innovative solutions to enhance decision-making, optimize water treatment processes, and ultimately improve environmental outcomes. Through the coverage of advanced computational techniques, such as data analysis, machine learning, and optimization strategies, readers will gain a deep understanding of how computational automation can revolutionize decision-making, allowing for more informed choices in water quality monitoring, pollution control, and resource allocation. This book is an invaluable resource for professionals, researchers, and policymakers seeking to stay at the forefront of water quality management practices, harnessing the power of computational automation for a cleaner, healthier future.

Details zur Ausgabe

• Verlag: Elsevier
• Erscheinungsdatum: 2025
• Sprache: Englisch
• ISBN 10: 0443333211
• ISBN 13: 9780443333217
• Einband: Taschenbuch
• Auflage: 1
• Anzahl der Seiten: 498
• Herausgeber: Dubey
• Kontakt zum Hersteller: ELSEVIER; https://www.elsevier.com/es-es; ; Mooswaldallee 6; Freiburg; 79108; Deutschland