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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Prima edizione
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Aggiungi al carrelloCondizione: New. 2026. 1st Edition. hardcover. . . . . .
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2026
ISBN 10: 1032709189 ISBN 13: 9781032709185
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Aggiungi al carrelloHardback. Condizione: New. Deep Learning Applications in Operations Research explores cutting-edge applications of deep learning and optimization techniques across various domains. By exploring innovative approaches and emerging trends in advanced intelligent applications, the book examines how innovation and emerging technologies can be leveraged to drive intelligent solutions across diverse domains. It covers such key areas as follows:A comparative study of deep learning algorithms and genetic algorithms as stochastic optimizers, analyzing their effectiveness in operations research applicationsAn updated approach to the critical path method (CPM) that combines traditional scheduling with modern computational methods for dynamic project environmentsA bibliometric analysis of smart warehousing trends in logistics operations management using R, providing data- driven insights into industry developmentsAn examination of edge computing optimization for real-time decision-making in operations research, focusing on latency reduction and computational efficiencyDevelopment of a hybrid intrusion detection system for IoT networks, combining machine learning with anomaly and signature-based detection approachesIntroduction of SAI-GAN, a novel approach for masked face reconstruction, paired with a DCNN-ELM classifier for enhanced biometric authenticationAnalysis of deep learning-driven mHealth applications in India's healthcare system, demonstrating how predictive analytics and real-time monitoring can improve healthcare accessibilityExploration of machine learning-driven ontology evolution in multi-tenant cloud architectures, advancing automated knowledge engineering through deep learning modelsProviding a wide-ranging overview of the field, the book helps researchers navigate the rapidly evolving landscape of advanced intelligent applications. It demonstrates the transformative impact of deep learning on operations research by offering practical insights and establishing a foundation for future innovations.
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ISBN 10: 1032709189 ISBN 13: 9781032709185
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Aggiungi al carrelloHardback. Condizione: New. Deep Learning Applications in Operations Research explores cutting-edge applications of deep learning and optimization techniques across various domains. By exploring innovative approaches and emerging trends in advanced intelligent applications, the book examines how innovation and emerging technologies can be leveraged to drive intelligent solutions across diverse domains. It covers such key areas as follows:A comparative study of deep learning algorithms and genetic algorithms as stochastic optimizers, analyzing their effectiveness in operations research applicationsAn updated approach to the critical path method (CPM) that combines traditional scheduling with modern computational methods for dynamic project environmentsA bibliometric analysis of smart warehousing trends in logistics operations management using R, providing data- driven insights into industry developmentsAn examination of edge computing optimization for real-time decision-making in operations research, focusing on latency reduction and computational efficiencyDevelopment of a hybrid intrusion detection system for IoT networks, combining machine learning with anomaly and signature-based detection approachesIntroduction of SAI-GAN, a novel approach for masked face reconstruction, paired with a DCNN-ELM classifier for enhanced biometric authenticationAnalysis of deep learning-driven mHealth applications in India's healthcare system, demonstrating how predictive analytics and real-time monitoring can improve healthcare accessibilityExploration of machine learning-driven ontology evolution in multi-tenant cloud architectures, advancing automated knowledge engineering through deep learning modelsProviding a wide-ranging overview of the field, the book helps researchers navigate the rapidly evolving landscape of advanced intelligent applications. It demonstrates the transformative impact of deep learning on operations research by offering practical insights and establishing a foundation for future innovations.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 264 pages. 9.18x6.12x9.45 inches. In Stock.
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ISBN 10: 1032709189 ISBN 13: 9781032709185
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Aggiungi al carrellohardcover. Condizione: New.
ISBN 10: 1032709189 ISBN 13: 9781032709185
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. Deep Learning Applications in Operations Research explores cutting-edge applications of deep learning and optimization techniques across various domains. By exploring innovative approaches and emerging trends in advanced intelligent applications, the book examines how innovation and emerging technologies can be leveraged to drive intelligent solutions across diverse domains. It covers such key areas as follows:A comparative study of deep learning algorithms and genetic algorithms as stochastic optimizers, analyzing their effectiveness in operations research applicationsAn updated approach to the critical path method (CPM) that combines traditional scheduling with modern computational methods for dynamic project environmentsA bibliometric analysis of smart warehousing trends in logistics operations management using R, providing data- driven insights into industry developmentsAn examination of edge computing optimization for real-time decision-making in operations research, focusing on latency reduction and computational efficiencyDevelopment of a hybrid intrusion detection system for IoT networks, combining machine learning with anomaly and signature-based detection approachesIntroduction of SAI-GAN, a novel approach for masked face reconstruction, paired with a DCNN-ELM classifier for enhanced biometric authenticationAnalysis of deep learning-driven mHealth applications in Indias healthcare system, demonstrating how predictive analytics and real-time monitoring can improve healthcare accessibilityExploration of machine learning-driven ontology evolution in multi-tenant cloud architectures, advancing automated knowledge engineering through deep learning modelsProviding a wide-ranging overview of the field, the book helps researchers navigate the rapidly evolving landscape of advanced intelligent applications. It demonstrates the transformative impact of deep learning on operations research by offering practical insights and establishing a foundation for future innovations. Emphasizing practical implementation, this book features real-world use cases, industry applications, and success stories. It examines how intelligent applications are transforming industries such as healthcare, finance, manufacturing, and transportation. 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: 1032709189 ISBN 13: 9781032709185
Da: CitiRetail, Stevenage, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Deep Learning Applications in Operations Research explores cutting-edge applications of deep learning and optimization techniques across various domains. By exploring innovative approaches and emerging trends in advanced intelligent applications, the book examines how innovation and emerging technologies can be leveraged to drive intelligent solutions across diverse domains. It covers such key areas as follows:A comparative study of deep learning algorithms and genetic algorithms as stochastic optimizers, analyzing their effectiveness in operations research applicationsAn updated approach to the critical path method (CPM) that combines traditional scheduling with modern computational methods for dynamic project environmentsA bibliometric analysis of smart warehousing trends in logistics operations management using R, providing data- driven insights into industry developmentsAn examination of edge computing optimization for real-time decision-making in operations research, focusing on latency reduction and computational efficiencyDevelopment of a hybrid intrusion detection system for IoT networks, combining machine learning with anomaly and signature-based detection approachesIntroduction of SAI-GAN, a novel approach for masked face reconstruction, paired with a DCNN-ELM classifier for enhanced biometric authenticationAnalysis of deep learning-driven mHealth applications in Indias healthcare system, demonstrating how predictive analytics and real-time monitoring can improve healthcare accessibilityExploration of machine learning-driven ontology evolution in multi-tenant cloud architectures, advancing automated knowledge engineering through deep learning modelsProviding a wide-ranging overview of the field, the book helps researchers navigate the rapidly evolving landscape of advanced intelligent applications. It demonstrates the transformative impact of deep learning on operations research by offering practical insights and establishing a foundation for future innovations. Emphasizing practical implementation, this book features real-world use cases, industry applications, and success stories. It examines how intelligent applications are transforming industries such as healthcare, finance, manufacturing, and transportation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 264 pages. 9.18x6.12x9.45 inches. In Stock. This item is printed on demand.
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EUR 230,01
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Emphasizing practical implementation, this book features real-world use cases, industry applications, and success stories. It examines how intelligent applications are transforming industries such as healthcare, finance, manufacturing, and transportation.
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Aggiungi al carrelloBuch. Condizione: Neu. Deep Learning Applications in Operations Research | Sanjay Misra (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Routledge | EAN 9781032709185 | 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: 1032709189 ISBN 13: 9781032709185
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 344,28
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Deep Learning Applications in Operations Research explores cutting-edge applications of deep learning and optimization techniques across various domains. By exploring innovative approaches and emerging trends in advanced intelligent applications, the book examines how innovation and emerging technologies can be leveraged to drive intelligent solutions across diverse domains. It covers such key areas as follows:A comparative study of deep learning algorithms and genetic algorithms as stochastic optimizers, analyzing their effectiveness in operations research applicationsAn updated approach to the critical path method (CPM) that combines traditional scheduling with modern computational methods for dynamic project environmentsA bibliometric analysis of smart warehousing trends in logistics operations management using R, providing data- driven insights into industry developmentsAn examination of edge computing optimization for real-time decision-making in operations research, focusing on latency reduction and computational efficiencyDevelopment of a hybrid intrusion detection system for IoT networks, combining machine learning with anomaly and signature-based detection approachesIntroduction of SAI-GAN, a novel approach for masked face reconstruction, paired with a DCNN-ELM classifier for enhanced biometric authenticationAnalysis of deep learning-driven mHealth applications in Indias healthcare system, demonstrating how predictive analytics and real-time monitoring can improve healthcare accessibilityExploration of machine learning-driven ontology evolution in multi-tenant cloud architectures, advancing automated knowledge engineering through deep learning modelsProviding a wide-ranging overview of the field, the book helps researchers navigate the rapidly evolving landscape of advanced intelligent applications. It demonstrates the transformative impact of deep learning on operations research by offering practical insights and establishing a foundation for future innovations. Emphasizing practical implementation, this book features real-world use cases, industry applications, and success stories. It examines how intelligent applications are transforming industries such as healthcare, finance, manufacturing, and transportation. 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.