Results 1 to 10 of about 8,402,433 (327)
A topology-based evaluation of resilience on urban road networks against epidemic spread: Implications for COVID-19 responses [PDF]
Frontiers in Public Health, 2022 Road closure is an effective measure to reduce mobility and prevent the spread of an epidemic in severe public health crises. For instance, during the peak waves of the global COVID-19 pandemic, many countries implemented road closure policies, such as ...
Junqing Tang +5 more
doaj +2 more sources
Relational Fusion Networks: Graph Convolutional Networks for Road Networks [PDF]
IEEE Transactions on Intelligent Transportation Systems, 2022 The application of machine learning techniques in the setting of road networks holds the potential to facilitate many important intelligent transportation applications. Graph Convolutional Networks (GCNs) are neural networks that are capable of leveraging the structure of a network.
Tobias Skovgaard Jepsen +2 more
openaire +4 more sources
A network percolation-based contagion model of flood propagation and recession in urban road networks. [PDF]
Sci Rep, 2020 In this study, we propose a contagion model as a simple and powerful mathematical approach for predicting the spatial spread and temporal evolution of the onset and recession of floodwaters in urban road networks.
Fan C, Jiang X, Mostafavi A.
europepmc +3 more sources
Local floods induce large-scale abrupt failures of road networks. [PDF]
Nat Commun, 2019 The adverse effect of climate change continues to expand, and the risks of flooding are increasing. Despite advances in network science and risk analysis, we lack a systematic mathematical framework for road network percolation under the disturbance of ...
Wang W, Yang S, Stanley HE, Gao J.
europepmc +2 more sources
Graph Convolutional Networks for Road Networks [PDF]
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019 Machine learning techniques for road networks hold the potential to facilitate many important transportation applications. Graph Convolutional Networks (GCNs) are neural networks that are capable of leveraging the structure of a road network by utilizing information of, e.g., adjacent road segments.
Jepsen, Tobias Skovgaard +2 more
semanticscholar +6 more sources
Bounded Asymmetry in Road Networks. [PDF]
Sci Rep, 2019 AbstractRoad networks are a classical stage for applications in network science and graph theory. Meanwhile, many combinatorial problems that arise in road networks are computationally intractable. Thus, an attractive way of tackling them is through efficient heuristics with provable performance guarantees, better known as approximation algorithms ...
Martínez Mori JC, Samaranayake S.
europepmc +3 more sources
Statistical Characteristics and Community Analysis of Urban Road Networks [PDF]
Complexity, 2020 Urban road networks are typical complex systems, which are crucial to our society and economy. In this study, topological characteristics of a number of urban road networks purely based on physical roads rather than routes of vehicles or buses are ...
Wen-Long Shang +5 more
doaj +2 more sources
Research on Urban Ecological Network Under the Threat of Road Networks—A Case Study of Wuhan
ISPRS International Journal of Geo-Information, 2019 The creation of a road network can lead to the fragmentation and reduction of the connectivity of the ecological habitat. The study of urban ecological networks under threat from rapidly developing road networks is of great significance in understanding ...
Zuohua Miao +5 more
doaj +2 more sources
Distributed Cooperative Driving in Multi-Intersection Road Networks [PDF]
IEEE Transactions on Vehicular Technology, 2021 Cooperative driving at isolated intersections attracted great interest and had been well discussed in recent years. However, cooperative driving in multi-intersection road networks remains to be further investigated, because many algorithms for isolated ...
Huaxin Pei +4 more
semanticscholar +1 more source
Sustainability, 2022 The digital transformation of engineering assets has been receiving increased attention from the scientific community in the last few years. In this regard, Digital Twins (DTs) have been widely applied in the industry and are now reaching the civil ...
João Vieira +4 more
semanticscholar +1 more source