AI and Machine Learning for Mechanical and Electrical Engineering (Innovations in Intelligent Internet of Everything) - Hardcover
Inhaltsangabe
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.
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Über die Autorin bzw. den Autor
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.
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AI and Machine Learning for Mechanical and Electrical Engineering
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Hardcover. Zustand: 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. Bestandsnummer des Verkäufers 9781032759487
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AI and Machine Learning for Mechanical and Electrical Engineering (Hardcover)
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Hardcover. Zustand: 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. Bestandsnummer des Verkäufers 9781032759487
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