Network-wide traffic signal control based on the discovery of critical nodes and deep reinforcement learning

M Xu, J Wu, L Huang, R Zhou, T Wang… - Journal of Intelligent …, 2020 - Taylor & Francis
To improve the traffic efficiency of city-wide road networks, we propose a traffic signal control
framework that prioritizes the optimal control policies on critical nodes in road networks. In …

Betweenness centrality in some classes of graphs

SK Raghavan Unnithan, B Kannan… - International Journal …, 2014 - Wiley Online Library
There are several centrality measures that have been introduced and studied for real‐world
networks. They account for the different vertex characteristics that permit them to be ranked …

Social network analysis approach for improved transportation planning

IH El-Adaway, IS Abotaleb, E Vechan - Journal of Infrastructure …, 2017 - ascelibrary.org
Social network analysis (SNA) is a well-established methodology for investigating networks
through the use of mathematical formulations abstracted from graph theory. It has been …

Leveraging social network analysis for characterizing cohesion of human-managed animals

D Vimalajeewa, S Balasubramaniam… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Social network analysis (SNA) is a technique to study behavioral dynamics within a social
group. In SNA, it is an open question whether it is possible to characterize animal-level …

Adaptive multi-agent deep mixed reinforcement learning for traffic light control

L Li, R Zhu, S Wu, W Ding, M Xu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Despite significant advancements in Multi-Agent Deep Reinforcement Learning (MADRL)
approaches for Traffic Light Control (TLC), effectively coordinating agents in diverse traffic …

Information technology project portfolio implementation process optimization based on complex network theory and entropy

Q Wang, G Zeng, X Tu - Entropy, 2017 - mdpi.com
In traditional information technology project portfolio management (ITPPM), managers often
pay more attention to the optimization of portfolio selection in the initial stage. In fact, during …

A Group-Based Distance Learning Method for Semisupervised Fuzzy Clustering

X Jing, Z Yan, Y Shen, W Pedrycz… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Learning a proper distance for clustering from prior knowledge falls into the realm of
semisupervised fuzzy clustering. Although most existing learning methods take prior …

Correlation of road network structure and urban mobility intensity: An exploratory study using geo-tagged tweets

L Geng, K Zhang - ISPRS International Journal of Geo-Information, 2022 - mdpi.com
Urban planners have been long interested in understanding how urban structure and
activities are mutually influenced. Human mobility and economic activities naturally drive the …

Identifying the most critical transportation intersections using social network analysis

IH El-Adaway, I Abotaleb, E Vechan - Transportation planning and …, 2018 - Taylor & Francis
Traffic congestion negatively impacts our society. Most of the traditional transportation
planning techniques–though effective–require rigorous amounts of data and analysis which …

A road network simplification algorithm that preserves topological properties

J Pung, RM D'Souza, D Ghosal, M Zhang - Applied Network Science, 2022 - Springer
A road network can be represented as a weighted directed graph with the nodes being the
traffic intersections, the edges being the road segments, and the weights being some …