面向平行应急管理高效能仿真方法

Research on High Efficiency Simulation Method for Parallel Emergency Management

基于人工社会的应急管理建模与仿真系统具有大规模、领域知识动态、多样异质、复杂时空演化等特点,给"预测-应对"型应急管理仿真带来了极大的挑战。针对面向平行应急管理仿真的特点,分析应急管理对仿真平台功能要求,对基于知识的人工社会初始场景构建、基于半监督机器学习的应急管理仿真建模、基于自组织增量学习的仿真模型在线评估,以及仿真云中的并行作业调度方法等方面进行了研究。在公共安全风险防控领域,对大规模社会媒体网络用户群体行为进行仿真,并对群体异常行为进行检测。通过社会媒体网络仿真应用实例,验证了高效能仿真平台的先进仿真手段能有效提升平行应急管理仿真能力。

The emergency management modeling and simulation system based on artificial social computational experiments has the characteristics of large-scale, domain knowledge dynamics, heterogeneity, complex space-time evolution, and so on, which brings great challenges to the "predictive-response" emergency management simulation. For the above challenges, we analyze the requirements of the parallel emergency management simulation platform, and discuss the high-performance simulation methods including the knowledge-based initial artificial social scene construction, the emergency management simulation modeling based on semi-supervised machine learning, the online evaluation of simulation model based on self-organized incremental learning, and the parallel job scheduling of the simulation cloud. The application of the abnormal behavior detection in the social media network can be used to prove that the advanced simulation methods of high-performance simulation platform can improve the parallel emergency management simulation capability.