Neural Networks and Graph Models for Traffic and Energy Systems (Hardcover)

Pankaj Bhambri

/ ISBN 13: 9798337302904

Edité par IGI Global, Hershey, 2025

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. N° de réf. du vendeur 9798337302904

Synopsis :

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.

À propos de l?auteur: Dr. Pankaj Bhambri is affiliated with the Department of Information Technology at Guru Nanak Dev Engineering College in Ludhiana. Additionally, he fulfills the role of the Institute's Coordinator for the Skill Enhancement Cell and acts as the Convener for his Departmental Board of Studies. He possesses nearly two decades of teaching experience. Dr. Bhambri acquired a Master of Technology degree in Computer Science and Engineering and a Bachelor of Engineering degree in Information Technology with Honours from I.K.G. Punjab Technical University in Jalandhar, India, and Dr. B.R. Ambedkar University in Agra, India, respectively. Dr. Bhambri obtained a Doctorate in Computer Science and Engineering from I.K.G. Punjab Technical University, located in Jalandhar, India. Over an extended period, he fulfilled many responsibilities including those of an Assistant Registrar (Academics), Member (Academic Council/BoS/DAB/RAC), Hostel Warden, APIO, and NSS Coordinator within his institution. His research work has been published in esteemed worldwide and national journals, as well as conference proceedings. Dr. Bhambri has made significant contributions to the academic field through his role as both an editor and author of various textbooks. Additionally, he has demonstrated his innovative thinking by filing several patents. Dr. Bhambri has received numerous prestigious awards from esteemed organizations in recognition of his exceptional achievements in both social and academic/research domains. These accolades include the ISTE Best Teacher Award in 2022 and 2023, the I2OR National Award in 2020, the Green ThinkerZ Top 100 International Distinguished Educators award in 2020, the I2OR Outstanding Educator Award in 2019, the SAA Distinguished Alumni Award in 2012, the CIPS Rashtriya Rattan Award in 2008, the LCHC Best Teacher Award in 2007, and several other commendations from various government and non-profit entities. He has provided guidance and oversight for numerous research projects and dissertations at the undergraduate, postgraduate, and Ph.D. levels. He successfully organized a diverse range of educational programmes, securing financial backing from esteemed institutions such as the All India Council for Technical Education (AICTE), the Technical Education Quality Improvement Programme (TEQIP), among others. Dr. Bhambri's areas of interest encompass machine learning, bioinformatics, wireless sensor networks, and network security. Dr. Bhambri possesses a wide array of professional responsibilities, encompassing the duties of an educator, editor, author, reviewer, expert speaker, motivator, and technical committee member for esteemed national and worldwide organizations.

Détails bibliographiques

Titre : Neural Networks and Graph Models for Traffic...
Éditeur : IGI Global, Hershey
Date d'édition : 2025
Reliure : Hardcover
Etat : new