Urban Network

Urban network research focuses on modeling and analyzing the complex interactions within cities, aiming to understand and optimize various aspects like traffic flow, communication networks, and socio-economic dynamics. Current research employs graph-based models, deep learning (including convolutional neural networks and diffusion models), and answer set programming to address challenges such as predicting gentrification, optimizing traffic distribution, and generating realistic origin-destination matrices. These advancements offer valuable tools for urban planning, resource allocation, and improving the efficiency and livability of cities.