Rakhi mutha (20 risultati)

Condizione: New.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. 2026. 1st Edition. hardcover. . . . . .

Hardback. 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.…

Condizione: New. 2026. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Condizione: Brand New. 264 pages. 9.18x6.12x9.45 inches. In Stock.

Hardback. 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.…

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mutha RakhiRakhi Mutha has obtained M.Tech. in Computer Science. She is working as lecturer in College of Technology. She is currently doing research work in the field of Ad-hoc Networking. She is author of several research papers an.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Ad-hoc networks are the particular type of networks, which are established by using more than one node in a specific arbitrary way to connect each other. These types of network systems can works without the fixed infrastructure for networks. The special feature which tries to makes their deployment quick and in the easy way. An Ad-hoc network can be utilize to provide network facilities in the places, where not to possible to form a fixed network, and where it is a cost effective to implement fixed network. The rapid implementation in the areas without the infrastructure which is often implies that the network users must explore an area and also form teams that in turn coordinate between themselves to create a specific task force or a nice mission in network simulation, also we can have individual random mobility and group mobility and also motion along with preplanned routes. Mobility model can be have major effect on the selection of a routing technique can then effect performance.…

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.…

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 our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Condizione: Brand New. 264 pages. 9.18x6.12x9.45 inches. In Stock. This item is printed on demand.

Buch. 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. …

Buch. 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. …