Isbn: 9781032725451 - deep learning applications in operations research (advances in computational collective intelligence) (8 resultados)

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  • Idioma: Inglés

    Editorial: Auerbach Publications, 2026

    1032725451 / 9781032725451

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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  • Idioma: Inglés

    Editorial: Taylor and Francis Ltd, 2026

    1032725451 / 9781032725451

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    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Taylor and Francis Ltd, 2026

    1032725451 / 9781032725451

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, 2026

    1032725451 / 9781032725451

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 104,91

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    Paperback. Condición: Brand New. 274 pages. 7.01x0.62x10.00 inches. In Stock.

  • Idioma: Inglés

    Editorial: CRC Press, 2026

    1032725451 / 9781032725451

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 79,75

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    Condición: New. The model-based approach for carrying out the classification and identification of tasks has led to progression of the machine learning paradigm in diversified fields of technology. Deep Learning Applications in Operations Research presents.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd (Sales) Jul 2026, 2026

    1032725451 / 9781032725451

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    EUR 151,74

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    Taschenbuch. Condición: Neu. Neuware - The model-based approach for carrying out the classification and identification of tasks has led to progression of the machine learning paradigm in diversified fields of technology. Deep Learning Applications in Operations Research presents the varied applications of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomenon. Such fields as object classification, speech recognition, and face detection have sought extensive applications of artificial intelligence (AI) and machine learning as well. The application of AI and ML has also become increasingly common in the domains of agriculture, health sectors, and insurance.Operations research is the branch of mathematics used to perform many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects to aid in decision making. Arriving at the proper decision depends on a number of factors; this book examines how AI and ML can be used to model equations and define constraints to solve problems more easily and discover proper and valid solutions. This book also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost. Case studies examine how to streamline operations and unearth data to make better business decisions. The concepts presented in this book can bring about and guide unique research directions to the future application of AI-enabled technologies.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1032725451 / 9781032725451

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    EUR 59,42

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    Cantidad disponible: 1 disponibles

    Paperback. Condición: new. Paperback. The model-based approach for carrying out the classification and identification of tasks has led to progression of the machine learning paradigm in diversified fields of technology. Deep Learning Applications in Operations Research presents the varied applications of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomenon. Such fields as object classification, speech recognition, and face detection have sought extensive applications of artificial intelligence (AI) and machine learning as well. The application of AI and ML has also become increasingly common in the domains of agriculture, health sectors, and insurance.Operations research is the branch of mathematics used to perform many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects to aid in decision making. Arriving at the proper decision depends on a number of factors; this book examines how AI and ML can be used to model equations and define constraints to solve problems more easily and discover proper and valid solutions. This book also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost. Case studies examine how to streamline operations and unearth data to make better business decisions. The concepts presented in this book can bring about and guide unique research directions to the future application of AI-enabled technologies. The book delves into how to apply deep learning to areas of operations research. The book focuses on decision modeling and model optimization and features case studies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1032725451 / 9781032725451

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    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Condición: Nuevo

    EUR 109,56

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    Cantidad disponible: 1 disponibles

    Paperback. Condición: new. Paperback. The model-based approach for carrying out the classification and identification of tasks has led to progression of the machine learning paradigm in diversified fields of technology. Deep Learning Applications in Operations Research presents the varied applications of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomenon. Such fields as object classification, speech recognition, and face detection have sought extensive applications of artificial intelligence (AI) and machine learning as well. The application of AI and ML has also become increasingly common in the domains of agriculture, health sectors, and insurance.Operations research is the branch of mathematics used to perform many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects to aid in decision making. Arriving at the proper decision depends on a number of factors; this book examines how AI and ML can be used to model equations and define constraints to solve problems more easily and discover proper and valid solutions. This book also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost. Case studies examine how to streamline operations and unearth data to make better business decisions. The concepts presented in this book can bring about and guide unique research directions to the future application of AI-enabled technologies. The book delves into how to apply deep learning to areas of operations research. The book focuses on decision modeling and model optimization and features case studies. 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.