Mumtaz A. Qaisrani (11 results)

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  • Language: English

    Published by CRC Press, 2026

    1032850183 / 9781032850184

    • Hardcover

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  • Language: English

    Published by CRC Press, 2026

    1032850183 / 9781032850184

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  • Language: English

    Published by Taylor and Francis Ltd, 2026

    1032850183 / 9781032850184

    • Hardcover

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  • Language: English

    Published by Taylor and Francis Ltd, 2026

    1032850183 / 9781032850184

    • Hardcover

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  • Language: English

    Published by CRC Press, 2026

    1032850183 / 9781032850184

    • Hardcover

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  • Language: English

    Published by CRC Press, 2026

    1032850183 / 9781032850184

    • Hardcover

    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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  • Language: English

    Published by CRC Press, 2026

    1032850183 / 9781032850184

    • Hardcover

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  • Language: English

    Published by CRC Press Aug 2026, 2026

    1032850183 / 9781032850184

    • Hardcover

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Buch. Condition: Neu. Neuware - Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. Features - Provides a comprehensive overview of thermal energy storage methods and systems. - Explains AI's role in enhancing thermal energy storage. - Includes real-world case studies and discusses perspectives of how TES and AI contribute to sustainability. - Addresses the integration of AI with digital twin technology, showcasing how AI algorithms can enhance the predictive accuracy and operational efficiency of digital twins in TES applications. - Explores various AI-driven strategies and technologies that enhance the efficiency, reliability, and scalability of energy storage systems. This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts.…

  • Language: English

    Published by Taylor & Francis Ltd, London, 2026

    1032850183 / 9781032850184

    • Hardcover
    • Print on Demand

    Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    Hardcover. Condition: new. Hardcover. Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. FeaturesProvides a comprehensive overview of thermal energy storage methods and systems.Explains AI's role in enhancing thermal energy storage.Includes real-world case studies and discusses perspectives of how TES and AI contribute to sustainability.Addresses the integration of AI with digital twin technology, showcasing how AI algorithms can enhance the predictive accuracy and operational efficiency of digital twins in TES applications.Explores various AI-driven strategies and technologies that enhance the efficiency, reliability, and scalability of energy storage systems.This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Language: English

    Published by Taylor & Francis Ltd, London, 2026

    1032850183 / 9781032850184

    • Hardcover
    • Print on Demand

    Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Hardcover. Condition: new. Hardcover. Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. FeaturesProvides a comprehensive overview of thermal energy storage methods and systems.Explains AI's role in enhancing thermal energy storage.Includes real-world case studies and discusses perspectives of how TES and AI contribute to sustainability.Addresses the integration of AI with digital twin technology, showcasing how AI algorithms can enhance the predictive accuracy and operational efficiency of digital twins in TES applications.Explores various AI-driven strategies and technologies that enhance the efficiency, reliability, and scalability of energy storage systems.This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. 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.…

  • Language: English

    Published by Taylor & Francis Ltd, London, 2026

    1032850183 / 9781032850184

    • Hardcover
    • Print on Demand

    Seller: CitiRetail, Stevenage, United KingdomCitiRetail

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    Hardcover. Condition: new. Hardcover. Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. FeaturesProvides a comprehensive overview of thermal energy storage methods and systems.Explains AI's role in enhancing thermal energy storage.Includes real-world case studies and discusses perspectives of how TES and AI contribute to sustainability.Addresses the integration of AI with digital twin technology, showcasing how AI algorithms can enhance the predictive accuracy and operational efficiency of digital twins in TES applications.Explores various AI-driven strategies and technologies that enhance the efficiency, reliability, and scalability of energy storage systems.This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…