首页|Collective Movement Simulation:Methods and Applications

Collective Movement Simulation:Methods and Applications

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
Collective movement simulations are challenging and important in many areas,including life science,mathematics,physics,information science and public safety.In this survey,we provide a comprehensive review of the state-of-the-art techniques for collective movement simulations.We start with a discussion on certain concepts to help beginners understand it more systematically.Then,we analyze the intelligence among different collective objects and the emphasis in different fields.Next,we classify existing collective move-ment simulation methods into four categories according to their effects,namely versatility,accuracy,dynamic adaptability,and assess-ment feedback capability.Furthermore,we introduce five applications of layout optimization,emergency control,dispatching,un-manned systems,and other derivative applications.Finally,we summarize possible future research directions.

Collective movement simulationmultiple objectsmultiple disciplinesimulation effectcollective intelligence

Hua Wang、Xing-Yu Guo、Hao Tao、Ming-Liang Xu

展开 >

School of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450001,China

Engineering Research Center of Intelligent Swarm Systems,Ministry of Education,Zhengzhou 450001,China

National Supercomputing Center in Zhengzhou,Zhengzhou 450001,China

China Ship Development and Design Center,Wuhan 430060,China

展开 >

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Key Research and Development Program of ChinaNatural Science Foundation of Henan Province,ChinaChina Postdoctoral Science FoundationSpecial Project for COV-ID-19 Prevention and Control Emergency Tackling of Henan Science and Technology Department,ChinaNational Defense Basic Scientific Research,ChinaSocial Simulator(Zhengzhou)Major Science and Technology Infrastructure Construction Strategy Research,China

62072415620360102021YFB33015042023004104962019MM662530201100312000JCKY2020XXXB0282021HENZDA03

2024

10.1007/s11633-022-1405-5

机器智能研究(英文)
中国科学院自动化所

机器智能研究(英文)

CSTPCDEI
影响因子：0.49
ISSN：2731-538X
年,卷(期)：2024.21(3)
  • 295