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Machine Learning and AI Application for Shovel Loading Operation: Developing State-of-the-art AI & Deep Learning Framework for Real-time Monitoring to Optimize Operations - Brossura
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Shovel-truck systems are the most widely employed excavation and material handling systems for surface mining operations. During this process, a high-impact shovel loading operation (HISLO) produces large forces that cause extreme whole body vibrations (WBV) that can severely affect the safety and health of haul truck operators. The research for solution development of this HISLO problem involved the application of artificial intelligence and machine learning for implementing the impact force detection in real time for a multi-pass shovel loading operation. A detailed step-by-step procedure involved in the successful application of machine learning, deep learning, and artificial intelligence for this real-world problem has been provided in this book.This work was a pioneering effort for advancing knowledge and frontiers in addressing the WBV challenges in deploying heavy mining machinery in safe and healthy large surface mining environments. The smart and intelligent real-time monitoring system minimizes the impact force on truck surface, which in turn reduces the level of vibration on the operator, thus leading to a safer and healthier working mining environment.
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- EditoreLAP LAMBERT Academic Publishing
- Data di pubblicazione2021
- ISBN 10 620386059X
- ISBN 13 9786203860597
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero di pagine248
- Contatto del produttorenon disponibile
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Machine Learning and AI Application for Shovel Loading Operation
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LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620386059X
ISBN 13: 9786203860597
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ali DanishDr. Danish Ali (Ph.D. from Missouri S&T, Rolla, MO, USA), currently leading various research projects for Caterpillar, has vast research and development experience in application of artificial intelligence, deep learning, m. Codice articolo 478262467
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Machine Learning and AI Application for Shovel Loading Operation
Editore:
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620386059X
ISBN 13: 9786203860597
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Machine Learning and AI Application for Shovel Loading Operation
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LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620386059X
ISBN 13: 9786203860597
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Machine Learning and AI Application for Shovel Loading Operation
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LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620386059X
ISBN 13: 9786203860597
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Machine Learning and AI Application for Shovel Loading Operation
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LAP LAMBERT Academic Publishing Mai 2021, 2021
ISBN 10: 620386059X
ISBN 13: 9786203860597
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Shovel-truck systems are the most widely employed excavation and material handling systems for surface mining operations. During this process, a high-impact shovel loading operation (HISLO) produces large forces that cause extreme whole body vibrations (WBV) that can severely affect the safety and health of haul truck operators. The research for solution development of this HISLO problem involved the application of artificial intelligence and machine learning for implementing the impact force detection in real time for a multi-pass shovel loading operation. A detailed step-by-step procedure involved in the successful application of machine learning, deep learning, and artificial intelligence for this real-world problem has been provided in this book.This work was a pioneering effort for advancing knowledge and frontiers in addressing the WBV challenges in deploying heavy mining machinery in safe and healthy large surface mining environments. The smart and intelligent real-time monitoring system minimizes the impact force on truck surface, which in turn reduces the level of vibration on the operator, thus leading to a safer and healthier working mining environment. 248 pp. Englisch. Codice articolo 9786203860597
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Machine Learning and AI Application for Shovel Loading Operation
Editore:
LAP LAMBERT Academic Publishing Mai 2021, 2021
ISBN 10: 620386059X
ISBN 13: 9786203860597
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -Shovel-truck systems are the most widely employed excavation and material handling systems for surface mining operations. During this process, a high-impact shovel loading operation (HISLO) produces large forces that cause extreme whole body vibrations (WBV) that can severely affect the safety and health of haul truck operators. The research for solution development of this HISLO problem involved the application of artificial intelligence and machine learning for implementing the impact force detection in real time for a multi-pass shovel loading operation. A detailed step-by-step procedure involved in the successful application of machine learning, deep learning, and artificial intelligence for this real-world problem has been provided in this book.This work was a pioneering effort for advancing knowledge and frontiers in addressing the WBV challenges in deploying heavy mining machinery in safe and healthy large surface mining environments. The smart and intelligent real-time monitoring system minimizes the impact force on truck surface, which in turn reduces the level of vibration on the operator, thus leading to a safer and healthier working mining environment.Books on Demand GmbH, Überseering 33, 22297 Hamburg 248 pp. Englisch. Codice articolo 9786203860597
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Machine Learning and AI Application for Shovel Loading Operation : Developing State-of-the-art AI & Deep Learning Framework for Real-time Monitoring to Optimize Operations
Editore:
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 620386059X
ISBN 13: 9786203860597
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Shovel-truck systems are the most widely employed excavation and material handling systems for surface mining operations. During this process, a high-impact shovel loading operation (HISLO) produces large forces that cause extreme whole body vibrations (WBV) that can severely affect the safety and health of haul truck operators. The research for solution development of this HISLO problem involved the application of artificial intelligence and machine learning for implementing the impact force detection in real time for a multi-pass shovel loading operation. A detailed step-by-step procedure involved in the successful application of machine learning, deep learning, and artificial intelligence for this real-world problem has been provided in this book.This work was a pioneering effort for advancing knowledge and frontiers in addressing the WBV challenges in deploying heavy mining machinery in safe and healthy large surface mining environments. The smart and intelligent real-time monitoring system minimizes the impact force on truck surface, which in turn reduces the level of vibration on the operator, thus leading to a safer and healthier working mining environment. Codice articolo 9786203860597
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