Synopsis
The book examines issues involved in the transition from traditional mechanical and electrical engineering and their management systems to the new engineering paradigms created by the application of smart systems. It covers applications, methods to transition to smart engineering and management, and associated ethical implications.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Dr. T. Rajasanthosh Kumar is an associate professor of the Department of Mechanical Engineering at Oriental Institute of Science and Technology, Bhopal, India.
Dr. Surendra Reddy Vinta is an associate professor of the School of Computer Science and Engineering at VIT-AP University, Amaravati, India.
Dr. Sagar Dhanraj Pande is head of the School of Engineering and Technology at Pimpri Chinchwad University, Pune, Maharashtra, India.
Dr. Aditya Khamparia is an assistant professor and coordinator of the Department of Computer Science at Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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AI and Machine Learning for Mechanical and Electrical Engineering
Edité par
Auerbach Publications, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Neuf
Couverture rigide
Vendeur : Books Puddle, New York, NY, Etats-Unis
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EUR 164,94
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AI and Machine Learning for Mechanical and Electrical Engineering (Hardcover)
Edité par
Taylor & Francis Ltd, London, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Neuf
Couverture rigide
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. Practical and informative, AI and Machine Learning for Mechanical and Electrical Engineering examines how artificial intelligence (AI) is changing the status quo in mechanical engineering, electrical systems, and management. Real-world examples and case studies demonstrate the application of AI in such diverse settings as industry and policymaking. This book illustrates how AI is playing a crucial role in enhancing productivity and innovation in various industries. It discusses transition methods and the ethical implications of using AI in mechanical engineering. Chapter highlights include the following:Developing a smart algorithm to integrate fault detection and classificationAlgorithms to investigate different testing scenarios for various anomalies in electric motorsData fusion to detect and assess electromechanical damageNeural networks for rolling bearing fault diagnosisEvolutionary algorithms to optimize deep learning models for water industry forecastsAI-based anomaly detection and root-cause analysisAn overarching theme is the transition from traditional mechanical, electrical, and management systems to AI-enabled smart systems. The book helps readers make sense of the challenges of integrating smart systems. It equips engineers with theoretical understanding as well as insight based on hands-on expertise. It shows how to better link and automate systems and improve productivity. This book not only shows how to implement smart solutions now but also shows the way to a more intelligent, productive, and interconnected future. The book examines issues involved in the transition from traditional mechanical and electrical engineering and their management systems to the new engineering paradigms created by the application of smart systems. It covers applications, methods to transition to smart engineering and management, and associated ethical implications. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032759487
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AI and Machine Learning for Mechanical and Electrical Engineering
Edité par
Auerbach Publications, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Neuf
Couverture rigide
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Image d'archives
Ai and Machine Learning for Mechanical and Electrical Engineering
Edité par
Auerbach Publications, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Neuf
Couverture rigide
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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AI and Machine Learning for Mechanical and Electrical Engineering
Edité par
Auerbach Publications, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Neuf
Couverture rigide
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Image d'archives
Ai and Machine Learning for Mechanical and Electrical Engineering
Edité par
Auerbach Publications, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Neuf
Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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AI and Machine Learning for Mechanical and Electrical Engineering
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AI and Machine Learning for Mechanical and Electrical Engineering
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HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur GB-9781032759487
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Image d'archives
Ai and Machine Learning for Mechanical and Electrical Engineering
Edité par
Auerbach Publications, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Ancien ou d'occasion
Couverture rigide
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 50003073
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Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
Quantité disponible : 10 disponible(s)
Image d'archives
AI and Machine Learning for Mechanical and Electrical Engineering (Hardcover)
Edité par
Taylor & Francis Ltd, London, 2025
ISBN 10 : 1032759488
ISBN 13 : 9781032759487
Neuf
Couverture rigide
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. Practical and informative, AI and Machine Learning for Mechanical and Electrical Engineering examines how artificial intelligence (AI) is changing the status quo in mechanical engineering, electrical systems, and management. Real-world examples and case studies demonstrate the application of AI in such diverse settings as industry and policymaking. This book illustrates how AI is playing a crucial role in enhancing productivity and innovation in various industries. It discusses transition methods and the ethical implications of using AI in mechanical engineering. Chapter highlights include the following:Developing a smart algorithm to integrate fault detection and classificationAlgorithms to investigate different testing scenarios for various anomalies in electric motorsData fusion to detect and assess electromechanical damageNeural networks for rolling bearing fault diagnosisEvolutionary algorithms to optimize deep learning models for water industry forecastsAI-based anomaly detection and root-cause analysisAn overarching theme is the transition from traditional mechanical, electrical, and management systems to AI-enabled smart systems. The book helps readers make sense of the challenges of integrating smart systems. It equips engineers with theoretical understanding as well as insight based on hands-on expertise. It shows how to better link and automate systems and improve productivity. This book not only shows how to implement smart solutions now but also shows the way to a more intelligent, productive, and interconnected future. The book examines issues involved in the transition from traditional mechanical and electrical engineering and their management systems to the new engineering paradigms created by the application of smart systems. It covers applications, methods to transition to smart engineering and management, and associated ethical implications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781032759487
Acheter neuf
EUR 172,83
Expédition à EUR 42,67
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
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