Smart Innovations in Energy and Mechanical Systems

Springer, 2025

This book appeals to researchers and professionals working in the field of artificial neural networks. It offers insights into the application of neural networks in engineering contexts, providing valuable case studies and methodologies for those looking to bridge the gap between AI theory and practical engineering solutions. Engineers and technicians involved in additive manufacturing will find relevant content in this book. It covers advanced techniques and applications of 3D printing in aerospace and mechanical engineering, offering a unique perspective on how these technologies are shaping the future of manufacturing. The book caters to professionals and students focusing on machine learning and artificial intelligence, particularly in industrial applications. It demonstrates how these technologies are being integrated into energy systems and mechanical engineering, providing real-world examples and potential future directions. Robotics enthusiasts and engineers will benefit from the book's coverage of cutting-edge developments in industrial and aerospace robotics. It offers insights into autonomous systems, control algorithms, and the integration of robotics in smart manufacturing environments. Graduate and undergraduate students in STEM fields beyond traditional engineering, such as computer science or data science, will find value in the book's interdisciplinary approach. It showcases how advanced computational methods are applied to solve complex engineering problems. This book is of interest to enterprises that are involved in the implementation of green energy technologies, resource-saving technologies, and support the concept of decarbonization of the energy system.

• Curatore: Natalia Honchar, Olena Kozlova, Dmytro Pavlenko, Pavlo Tryshyn
• Anno edizione: 2025
• Editore: Springer
• Formato: EPUB3 con Adobe DRM
• Lingua: Inglese
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9783031951916