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Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 1041062893 ISBN 13: 9781041062899
Language: English
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Hardcover. Condition: new. Hardcover. The text covers emerging technologies and innovations in the field, such as hybrid solar thermal systems, advanced materials for collectors, novel heat storage solutions, and advancements in concentrating solar power (CSP) technologies. It presents artificial intelligence and machine learning techniques for solar thermal system optimization.Key Features:Discusses the use of smart technologies such as artificial intelligence and machine learning in transforming solar thermal systems by enhancing their efficiency, reliability, and cost-effectivenessProvides insights into optimization techniques for online testing of parameters for solar dryers, AI-based predictive modeling for accurate solar power generation, dual-axis solar panel tracking and monitoring systems, IoT in solar dryer design, and greenhouse-type solar dryer systemsCovers state-of-the-art computational models used in optimizing solar thermal systems, such as neural networks, genetic algorithms for predictive modeling, control strategies, and system optimizationPresents case studies and examples of implementations of computational intelligence and smart technologies in solar thermal applications, having real-time applications in a 4kW hybrid solar EV charging station, of five-level inverter for solar photovoltaic systems, agrivoltaic systems, and wind-solar-hydrogen hybrid energy generationIntroduces simulation and modeling tools used in the design, analysis, and performance evaluation of solar thermal collectors for decentralized cooking, next-generation solar power plants, and hybrid energy generation systemsThis book is primarily written for senior undergraduates, graduate students, and academic researchers in mechanical engineering, energy engineering, computer science and engineering, renewable energy, solar energy, and clean technologies. The text covers emerging technologies and innovations in fields such as hybrid solar thermal systems, advanced materials for collectors, novel heat storage solutions, and advancements in concentrating solar power (CSP) technologies. It presents artificial intelligence and machine learning techniques for solar thermal system optimization. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Taylor & Francis Ltd, 2025
ISBN 10: 1041062893 ISBN 13: 9781041062899
Language: English
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Published by Taylor and Francis Ltd, GB, 2025
ISBN 10: 1041062893 ISBN 13: 9781041062899
Language: English
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Hardback. Condition: New. The text covers emerging technologies and innovations in the field, such as hybrid solar thermal systems, advanced materials for collectors, novel heat storage solutions, and advancements in concentrating solar power (CSP) technologies. It presents artificial intelligence and machine learning techniques for solar thermal system optimization.Key Features:Discusses the use of smart technologies such as artificial intelligence and machine learning in transforming solar thermal systems by enhancing their efficiency, reliability, and cost-effectivenessProvides insights into optimization techniques for online testing of parameters for solar dryers, AI-based predictive modeling for accurate solar power generation, dual-axis solar panel tracking and monitoring systems, IoT in solar dryer design, and greenhouse-type solar dryer systemsCovers state-of-the-art computational models used in optimizing solar thermal systems, such as neural networks, genetic algorithms for predictive modeling, control strategies, and system optimizationPresents case studies and examples of implementations of computational intelligence and smart technologies in solar thermal applications, having real-time applications in a 4kW hybrid solar EV charging station, of five-level inverter for solar photovoltaic systems, agrivoltaic systems, and wind-solar-hydrogen hybrid energy generationIntroduces simulation and modeling tools used in the design, analysis, and performance evaluation of solar thermal collectors for decentralized cooking, next-generation solar power plants, and hybrid energy generation systemsThis book is primarily written for senior undergraduates, graduate students, and academic researchers in mechanical engineering, energy engineering, computer science and engineering, renewable energy, solar energy, and clean technologies.
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Published by Engineering Science Reference, 2017
ISBN 10: 1522536868 ISBN 13: 9781522536864
Language: English
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Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 1041062893 ISBN 13: 9781041062899
Language: English
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Add to basketHardcover. Condition: new. Hardcover. The text covers emerging technologies and innovations in the field, such as hybrid solar thermal systems, advanced materials for collectors, novel heat storage solutions, and advancements in concentrating solar power (CSP) technologies. It presents artificial intelligence and machine learning techniques for solar thermal system optimization.Key Features:Discusses the use of smart technologies such as artificial intelligence and machine learning in transforming solar thermal systems by enhancing their efficiency, reliability, and cost-effectivenessProvides insights into optimization techniques for online testing of parameters for solar dryers, AI-based predictive modeling for accurate solar power generation, dual-axis solar panel tracking and monitoring systems, IoT in solar dryer design, and greenhouse-type solar dryer systemsCovers state-of-the-art computational models used in optimizing solar thermal systems, such as neural networks, genetic algorithms for predictive modeling, control strategies, and system optimizationPresents case studies and examples of implementations of computational intelligence and smart technologies in solar thermal applications, having real-time applications in a 4kW hybrid solar EV charging station, of five-level inverter for solar photovoltaic systems, agrivoltaic systems, and wind-solar-hydrogen hybrid energy generationIntroduces simulation and modeling tools used in the design, analysis, and performance evaluation of solar thermal collectors for decentralized cooking, next-generation solar power plants, and hybrid energy generation systemsThis book is primarily written for senior undergraduates, graduate students, and academic researchers in mechanical engineering, energy engineering, computer science and engineering, renewable energy, solar energy, and clean technologies. The text covers emerging technologies and innovations in fields such as hybrid solar thermal systems, advanced materials for collectors, novel heat storage solutions, and advancements in concentrating solar power (CSP) technologies. It presents artificial intelligence and machine learning techniques for solar thermal system optimization. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Engineering Science Reference, 2017
ISBN 10: 1522536868 ISBN 13: 9781522536864
Language: English
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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