Häftad, Engelska, 2025
Del i serien Cognitive Data Science in Sustainable Computing
Artificial Intelligence in Future Mining
Av Amir Razmjou, Mohsen Asadnia
2049 kr
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Beskrivning
The book wraps up with chapters on safety and risk, resource planning, and a larger discussion of the opportunities and challenges of mining with AI in the future. This book is a must-have for researchers and professionals who find themselves at the intersection of mining, engineering, and data science.
- Provides high-level analyses as well as practical insights and real-world examples on the impact of AI on future mining
- Includes case studies on the application of data processing, the Internet of Things, and artificial intelligence in environmental sensing
- Provides in-depth discussion of the future implications of AI on the mining industry at the end of each chapter
Produktinformation
- Utgivningsdatum: 2025-01-24
- Mått: 152 x 229 x 21 mm
- Vikt: 710 g
- Format: Häftad
- Språk: Engelska
- Serie: Cognitive Data Science in Sustainable Computing
- Antal sidor: 440
- Förlag: Elsevier Science
- ISBN: 9780443289118
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Mer information
Amir Razmjou is an Associate Professor at Edith Cowan University and the Leader of the Mineral Recovery Research Centre (MRRC).Associate Professor Amir Razmjou (PhD from the University of New South Wales (UNSW), Sydney, Australia, 2012) is an experienced academic and industry professional with over 20 years of expertise in desalination, water treatment, membrane technology, and mineral processing. As a Board Director of the Membrane Society of Australasia (MSA) and Founder of the Mineral Recovery Research Centre (MRRC) at Edith CowanUniversity (ECU), Western Australia, Associate Professor Razmjou has made significant contributions to the fields of mining and resource extraction, particularly in lithium processing.He has published over 200 peer-reviewed articles and secured research funding exceeding $9.2 million AUD. Dr. Razmjou has received awards such as the 2024 WA FHRI Fund Innovation Fellow, the 2023 MSA Industry Innovation Award, and the 2021 UTS Chancellor Research Fellow. He has supervised more than 40 master’s and Ph.D. candidates and serves in editorial roles for journals such as Desalination, DWT, and JWPE. At MRRC, he has established a DLE line, including various processes such as membranes, ion exchange, and adsorption at laboratory and pilot scales. His research also includes developing and implementing advanced technologies for DLE’s pretreatment and posttreatment to enhance the Li/TDS ratio and purify the final product to battery-gradequality"Mohsen Asadnia is a Professor and group lader in Mechatronics-biomechanics and at Macquarie University, Australia. He received his PhD degree in Mechanical Engineering from Nanyang Technological University, Singapore. Prior to joining Macquarie University, Mohsen had several teaching and research roles with the University of Western Australia, Massachusetts Institute of Technology and Nanyang Technological University. His research interest lies in environmental/ biomedical sensors, Artificial Intelligence, and bio-inspired sensing.
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