欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
在CPS的应用背景下,对传感器和控制设备产生的不确定性事件流进行分析和处理得出高层事件,然后在此基础上引入适应性动态贝叶斯网络和并行马尔可夫决策过程模型来支持主动式的复杂事件处理。针对大型CPS中马尔可夫决策过程存在的状态数量巨大的问题,引入状态划分和报酬分解的方法来进行并行优化。在模拟交通网络的环境中,实验结果显示所提方法能有效地处理事件流,并具有良好的可扩展性。
英文摘要：
Based on the preliminary analysis results of the indeterminate event stream that generated by the sensors and control purpose equipment of CPS, the adaptive dynamic Bayesian network and parallel Markov decision process model were used to support the proactive complex event processing. In order to resolve the vast state space issue of Markov decision process for large CPS, states partition and reward decomposition methods were proposed to parallel the decision making process. The experimental result based on the simulation of traffic network shows that proposed method can process event stream effectively and has favorable scalability.
同期刊论文项目
同项目期刊论文
A simulated annealing based genetic local search algorithm for multi-objective multicast routing pro
期刊信息
位置：