Neural Networks and Graph Models for Traffic and Energy Systems
ISBN 13: 9798337302911
Published by Engineering Science Reference, 2025
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"This book presents advanced AI approaches and their practical applications in traffic and energy systems, expanding the limits of existing research and practice. It showcases the potential of neural networks and graph models to greatly improve the effectiveness and dependability of traffic control and energy distribution, resulting in more intelligent and environmentally friendly urban settings"-- Provided by publisher.
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Title: Neural Networks and Graph Models for Traffic...
Publisher: Engineering Science Reference
Publication Date: 2025
Binding: Soft cover
Condition: New
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Neural Networks and Graph Models for Traffic and Energy Systems
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Neural Networks and Graph Models for Traffic and Energy Systems (Paperback)
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Paperback. Condition: new. Paperback. Neural networks and graph models play a transformative role in optimizing traffic and energy systems, offering advanced solutions for managing complex, interconnected infrastructures. Neural networks can predict traffic patterns, optimize routes, and improve the efficiency of energy distribution networks by learning from real-time data. Graph models help represent and analyze the relationships and flows within transportation and energy systems, enabling more accurate modeling of networks and their interactions. Together, these technologies allow for smarter traffic management, reduced congestion, and enhanced energy grid efficiency. As cities and industries continue to grow, integrating neural networks and graph models into traffic and energy systems is essential in creating sustainable, efficient, and resilient urban environments. Neural Networks and Graph Models for Traffic and Energy Systems explores the sophisticated techniques and practical uses of artificial intelligence in improving and overseeing traffic and energy networks. It examines the connection between neural networks and graph theory, showing how these technologies might transform the effectiveness, sustainability, and robustness of urban infrastructure. This book covers topics such as sustainable development, energy science, traffic systems, and is a useful resource for energy scientists, computer engineers, urban developers, academicians, and researchers. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798337302911
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Neural Networks and Graph Models for Traffic and Energy Systems
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Taschenbuch. Condition: Neu. Neural Networks and Graph Models for Traffic and Energy Systems | Pankaj Bhambri (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798337302911 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 131667089
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Neural Networks and Graph Models for Traffic and Energy Systems (Paperback)
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Paperback. Condition: new. Paperback. Neural networks and graph models play a transformative role in optimizing traffic and energy systems, offering advanced solutions for managing complex, interconnected infrastructures. Neural networks can predict traffic patterns, optimize routes, and improve the efficiency of energy distribution networks by learning from real-time data. Graph models help represent and analyze the relationships and flows within transportation and energy systems, enabling more accurate modeling of networks and their interactions. Together, these technologies allow for smarter traffic management, reduced congestion, and enhanced energy grid efficiency. As cities and industries continue to grow, integrating neural networks and graph models into traffic and energy systems is essential in creating sustainable, efficient, and resilient urban environments. Neural Networks and Graph Models for Traffic and Energy Systems explores the sophisticated techniques and practical uses of artificial intelligence in improving and overseeing traffic and energy networks. It examines the connection between neural networks and graph theory, showing how these technologies might transform the effectiveness, sustainability, and robustness of urban infrastructure. This book covers topics such as sustainable development, energy science, traffic systems, and is a useful resource for energy scientists, computer engineers, urban developers, academicians, and researchers. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798337302911
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Neural Networks and Graph Models for Traffic and Energy Systems (Paperback)
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Paperback. Condition: new. Paperback. Neural networks and graph models play a transformative role in optimizing traffic and energy systems, offering advanced solutions for managing complex, interconnected infrastructures. Neural networks can predict traffic patterns, optimize routes, and improve the efficiency of energy distribution networks by learning from real-time data. Graph models help represent and analyze the relationships and flows within transportation and energy systems, enabling more accurate modeling of networks and their interactions. Together, these technologies allow for smarter traffic management, reduced congestion, and enhanced energy grid efficiency. As cities and industries continue to grow, integrating neural networks and graph models into traffic and energy systems is essential in creating sustainable, efficient, and resilient urban environments. Neural Networks and Graph Models for Traffic and Energy Systems explores the sophisticated techniques and practical uses of artificial intelligence in improving and overseeing traffic and energy networks. It examines the connection between neural networks and graph theory, showing how these technologies might transform the effectiveness, sustainability, and robustness of urban infrastructure. This book covers topics such as sustainable development, energy science, traffic systems, and is a useful resource for energy scientists, computer engineers, urban developers, academicians, and researchers. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798337302911
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Neural Networks and Graph Models for Traffic and Energy Systems
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Neural Networks and Graph Models for Traffic and Energy Systems (Hardcover)
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Hardcover. Condition: new. Hardcover. Neural networks and graph models play a transformative role in optimizing traffic and energy systems, offering advanced solutions for managing complex, interconnected infrastructures. Neural networks can predict traffic patterns, optimize routes, and improve the efficiency of energy distribution networks by learning from real-time data. Graph models help represent and analyze the relationships and flows within transportation and energy systems, enabling more accurate modeling of networks and their interactions. Together, these technologies allow for smarter traffic management, reduced congestion, and enhanced energy grid efficiency. As cities and industries continue to grow, integrating neural networks and graph models into traffic and energy systems is essential in creating sustainable, efficient, and resilient urban environments. Neural Networks and Graph Models for Traffic and Energy Systems explores the sophisticated techniques and practical uses of artificial intelligence in improving and overseeing traffic and energy networks. It examines the connection between neural networks and graph theory, showing how these technologies might transform the effectiveness, sustainability, and robustness of urban infrastructure. This book covers topics such as sustainable development, energy science, traffic systems, and is a useful resource for energy scientists, computer engineers, urban developers, academicians, and researchers. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798337302904