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portada AI and Machine Learning for Mechanical and Electrical Engineering
Type
Physical Book
Publisher
Collection
Innovations in Intelligent Internet of Everything IoE
Year
2025
Pages
321
Format
Hardcover
Dimensions
23.40 x 15.60 cm
ISBN13
9781032759487

AI and Machine Learning for Mechanical and Electrical Engineering

Aditya Khamparia;T. Rajasanthosh Kumar;Surendra Reddy Vinta;Sagar Dhanraj Pande (Author) · Auerbach · Hardcover

AI and Machine Learning for Mechanical and Electrical Engineering - Aditya Khamparia;T. Rajasanthosh Kumar;Surendra Reddy Vinta;Sagar Dhanraj Pande

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Synopsis "AI and Machine Learning for Mechanical and Electrical Engineering"

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.

Practical and informative, AI and Machine Learning for Mechanical and Electrical Engineering examines how 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. Highlights include:

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 analysis.

An 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.

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