Quan Shi – författare

This book delves into the problems and challenges faced in achieving improved performance in connected vehicles traffic flow prediction in intelligent connected transportation systems and provides an in-depth analysis of spatial-temporal feature extraction, global local spatial feature extraction, and fusion of external factors. The book is divided into ten chapters, and the introductory section presents the history of the development of artificial intelligence and graph neural networks in the context of connected vehicles, related work on prediction of connected traffic, and preliminary knowledge. Chapter 2 to 9 present eight prediction methods in the context of connected traffic, respectively. Each section includes an introduction to the problem definition, model architecture, experimental setup, and discussion of results, as well as references. The last section summarizes the contributions of the book and future challenges.

Chemical structure and bonding. The scope of the series spans the entire Periodic Table and addresses structure and bonding issues associated with all of the elements. It also focuses attention on new and developing areas of modern structural and theoretical chemistry such as nanostructures, molecular electronics, designed molecular solids, surfaces, metal clusters and supramolecular structures. Physical and spectroscopic techniques used to determine, examine and model structures fall within the purview of Structure and Bonding to the extent that the focus is on the scientific results obtained and not on specialist information concerning the techniques themselves. Issues associated with the development of bonding models and generalizations that illuminate the reactivity pathways and rates of chemical processes are also relevant. The individual volumes in the series are thematic. The goal of each volume is to give the reader, whether at a university or in industry, a comprehensive overview of an area where new insights are emerging that are of interest to a larger scientific audience.