Smart Electrical and Mechanical Systems: An Application of Artificial Intelligence and Machine Learning

Smart Electrical and Mechanical Systems: An Application of Artificial Intelligence and Machine Learning is an international contributed work with the most up-to-date fundamentals and conventional methods used in smart electrical and mechanical systems. Detailing methods and procedures for the application of ML and AI, it is supported with illustrations of the systems, process diagrams visuals of the systems and/or their components, and supportive data and results leading to the benefits and challenges of the relevant applications. The multidisciplinary theme of the book will help researchers build a synergy between electrical and mechanical engineering systems. The book guides readers on not only how to effectively solve problems but also provide high accuracy needed for successful implementation. Interdisciplinary in nature, the book caters to the needs of the electrical and mechanical engineering industry by offering details on the application of AI and ML in robotics, design and manufacturing, image processing, power system operation and forecasting with suitable examples. Includes significant case studies related to application of Artificial Intelligence and Machine Learning in Energy and Power, Mechanical Design and Manufacturing Contains supporting illustrations and tables, along with a valuable set of references at the end of each chapter Provides original, state-of-the-art research material written by international and national respected contributors INDICE: 1. Basics of Artificial intelligence and Machine learning2. Artificial Intelligence and machine learning based Robot Control3. Smart Mechanical Design4. Smart Manufacturing5. Autonomous vehicles6. Image processing for electrical and mechanical engineering 7. Machine learning in smart electric power systems 8. Renewable energy integration with ML9. Machine learning applications in optimal power flow 10. Machine learning applications in power system control11. Machine learning applications in power system forecasting

• ISBN: 978-0-323-90789-7
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 410
• Fecha Publicación: 01/06/2022
• Nº Volúmenes: 1
• Idioma: Inglés