Abstract：To represent and reason uncertain knowledge in the complex system dynamically and effectively, a self-adaptive method based on fuzzy-Petri net (FPN) and genetic particle swarm optimization (GPSO) algorithm is proposed. In this method, the knowledge-representation model based on FPN is established to build the mathematical model. And the GPSO is used in self-learning of the uncertain parameters to achieve self-adaptation of the model. Finally, a servo mechanism fault diagnose of launch vehicle is used to verify the proposed method.
彭勋，王伟明，谷朝臣，胡洁. 基于模糊Petri网和Genetic-PSO算法的动态不确定性知识表示方法*[J]. 模式识别与人工智能, 2014, 27(10): 887-894.
PENG Xun, WANG Wei-Ming, GU Chao-Chen, HU Jie. Representation Method of Dynamic Uncertain Knowledge Based on Fuzzy-Petri Net and Genetic-PSO Algorithm. , 2014, 27(10): 887-894.
2014, Vol. 27 
