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Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.
This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered.
The very first book in Elsevier’s cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids.
Über die Autorinnen und Autoren:
Ashutosh Kumar Dubey is an Associate Professor in the Department of Computer Science and Engineering at Chitkara University, Himachal Pradesh, India. He is also a Postdoctoral Fellow of the Ingenium Research Group Lab, Universidad
de Castilla-La Mancha, Ciudad Real, Spain.
Dr Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science & Engineering at Chandigarh University, Punjab. He holds a PhD in Computer Science from the University of Madras and completed postdoctoral research at the Ingenium Research Group Lab, Universidad de Castilla-La Mancha, Spain. He brings extensive expertise in data science and AI-driven analytical modelling. He has published impactful research in reputed journals such as Expert Systems with Applications, Archives of Computational Methods in Engineering, and Scientific Reports, and has published books such as Computer Vision and Machine Intelligence for Renewable Energy Systems (Elsevier) and Quantum Protocols in Blockchain Security (Springer). His research areas are artificial intelligence, renewable energy, machine learning, and image processing.
Umesh Chandra Pati is a Professor in the Department of Electronics and Communication Engineering at the National Institute of Technology, India. He has authored/edited two books and published over 100 articles in peer-reviewed international journals and conference proceedings. He has also guest-edited special issues of Cognitive Neurodynamics and International Journal of Signal and Imaging System Engineering. Dr. Pati has filed 2 Indian patents. Besides other sponsored projects, he is currently associated with a high value IMPRINT project “Intelligent Surveillance Data Retriever (ISDR) for Smart City Applications”, an initiative of the Ministries of Education, and Housing and Urban Affairs in the Government of India. His current areas of research include Computer Vision, Artificial Intelligence, the Internet of Things (IoT), Industrial Automation, and Instrumentation Systems.
Titel: Computer Vision and Machine Intelligence for...
Verlag: Elsevier
Erscheinungsdatum: 2024
Einband: Softcover
Zustand: New
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Artikel-Nr. 394710869
Anzahl: 3 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systemsBuilds knowledge and tools in a systematic manner, from fundamentals to advanced applicationsIncludes dedicated chapters. Artikel-Nr. 1736147094
Anzahl: Mehr als 20 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. Artikel-Nr. 9780443289477
Anzahl: 2 verfügbar