Mapping the knowledge domain of soft computing applications for emergency evacuation studies: A scientometric analysis and critical review

B Liang, CN van der Wal, K Xie, Y Chen, FMT Brazier… - Safety science, 2023 - Elsevier
Emergency evacuation is viewed as a common strategy adopted during the disaster
preparedness stage of evacuation to ensure the safety of potentially affected populations. In …

A Gaussian type-2 fuzzy programming approach for multicrowd congestion-relieved evacuation planning

J Men, G Chen, P Chen, L Zhou - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Large-scale emergencies occur frequently around the world, causing serious casualties.
Emergency evacuation is one of the top priorities after a disaster. Due to the uncertain and …

[HTML][HTML] Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

W Fei, ZHU Xiaoping, Z Zhou, T Yang - Chinese Journal of Aeronautics, 2024 - Elsevier
In some military application scenarios, Unmanned Aerial Vehicles (UAVs) need to perform
missions with the assistance of on-board cameras when radar is not available and …

Evacuation-path-selection model of real-time fire diffusion in urban underground complexes

XJ Li, WB Chen, RX Chen, CT Chang… - Computers & Industrial …, 2023 - Elsevier
Evacuation in the event of a fire in an urban underground complexes (UUC) is a big
challenge. How to conduct limited evacuation in case of a fire in UUC is a problem worthy of …

Simulation of pedestrian evacuation with reinforcement learning based on a dynamic scanning algorithm

Z Huang, R Liang, Y Xiao, Z Fang, X Li, R Ye - Physica A: Statistical …, 2023 - Elsevier
Humans plan their movements mainly based on visual information. However, agents in few
existing evacuation models perceive the environment by using visual information. To obtain …

Crowd evacuation under real data: a crowd congestion control method based on sensors and knowledge graph

J Duan, H Liu, W Gong, L Lyu - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Crowd congestion is an important factor affecting evacuation efficiency, and reasonable
regulation of crowd congestion in the evacuation process is one way to improve crowd …

Deep reinforcement learning and 3D physical environments applied to crowd evacuation in congested scenarios

D Zhang, W Li, J Gong, G Zhang, J Liu… - … Journal of Digital …, 2023 - Taylor & Francis
To avoid crowd evacuation simulations depending on 2D environments and real data, we
propose a framework for crowd evacuation modeling and simulation by applying deep …

[HTML][HTML] An enhanced deep deterministic policy gradient algorithm for intelligent control of robotic arms

R Dong, J Du, Y Liu, AA Heidari… - Frontiers in …, 2023 - frontiersin.org
Aiming at the poor robustness and adaptability of traditional control methods for different
situation, the Deep Deterministic Policy Gradient (DDPG) algorithm is improved by …

[HTML][HTML] Calibration of pedestrian ingress model based on CCTV surveillance data using machine learning methods

M Pálková, O Uhlík, T Apeltauer - PLoS one, 2024 - journals.plos.org
Machine learning methods and agent-based models enable the optimization of the
operation of high-capacity facilities. In this paper, we propose a method for automatically …

[HTML][HTML] HDRLM3D: A deep reinforcement learning-based model with human-like perceptron and policy for crowd evacuation in 3D environments

D Zhang, W Li, J Gong, L Huang, G Zhang… - … International Journal of …, 2022 - mdpi.com
At present, a common drawback of crowd simulation models is that they are mainly
simulated in (abstract) 2D environments, which limits the simulation of crowd behaviors …