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Aggiungi al carrelloHardcover. Condizione: Brand New. 372 pages. 10.00x7.00x10.24 inches. In Stock.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041089694 ISBN 13: 9781041089698
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability.Exploring applications in sustainable energy systems, renewable resources, and smart grids, the book presents intelligent control methodologies, predictive modeling, real-time data analysis, and thermal management with deep learning. It covers AI-driven heat transfer monitoring, which is critical for a variety of applications beyond sustainability, including industrial production, aerospace, automotive, and electronics cooling. The chapters feature numerous case studies of AI/ML implementation in heat exchangers, power plants, and renewable energy systems.This book will interest researchers and graduate students studying the intersection of AI, ML, and heat transfer optimization as applied to energy systems. Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041089694 ISBN 13: 9781041089698
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability.Exploring applications in sustainable energy systems, renewable resources, and smart grids, the book presents intelligent control methodologies, predictive modeling, real-time data analysis, and thermal management with deep learning. It covers AI-driven heat transfer monitoring, which is critical for a variety of applications beyond sustainability, including industrial production, aerospace, automotive, and electronics cooling. The chapters feature numerous case studies of AI/ML implementation in heat exchangers, power plants, and renewable energy systems.This book will interest researchers and graduate students studying the intersection of AI, ML, and heat transfer optimization as applied to energy systems. Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Jatoth Heeraman is an Assistant Professor of Mechanical Engineering at Malla Reddy (MR) Deemed to be University, Hyderabad, India. He received his Ph.D. in Mechanical Engineering from Lovely Professional University, India in 2024 and earned hi.
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems | Jatoth Heeraman (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | CRC Press | EAN 9781041089698 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041089694 ISBN 13: 9781041089698
Da: AussieBookSeller, Truganina, VIC, Australia
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability.Exploring applications in sustainable energy systems, renewable resources, and smart grids, the book presents intelligent control methodologies, predictive modeling, real-time data analysis, and thermal management with deep learning. It covers AI-driven heat transfer monitoring, which is critical for a variety of applications beyond sustainability, including industrial production, aerospace, automotive, and electronics cooling. The chapters feature numerous case studies of AI/ML implementation in heat exchangers, power plants, and renewable energy systems.This book will interest researchers and graduate students studying the intersection of AI, ML, and heat transfer optimization as applied to energy systems. Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability.