改进的关联模式竞争求解算法

Improved connectionist model resolving algorithm

在利用概率因果网络模型进行故障诊断过程中,传统的计算方法不能直接得到诊断问题的解,且当故障节点较多或网络层次较多时,存在着"组合爆炸"、计算量呈指数速度增加等问题。本文提出了以因果网络理论为基础的关联模式竞争求解算法,并对该算法进行了改进。改进后的算法解决了多层次、多节点的复杂因果网络模型推理难题,降低了诊断复杂度。最后通过一个实例验证了此方法的优越性及工程实用性。

In the procedure of fault diagnosis by probabilistic causal network model,the solution of the diagnostic problem can not be directly gotten by the traditional reasoning algorithm,furthermore,multi-level,multi-node complicated causal network may lead to the problem of＂combinatorial explosion＂and the exponential increase in computational cost etc.The competition-based connectionist model reasoning algorithm based on probabilistic causal network is put forward and the algorithm is modified.The problem of multi-level,multi-node complicated causal network reasoning is solved by the algorithm presented,and the complexity of the diagnosis is reduced.Finally,the advantages and the engineering practicability are demonstrated by a practical example.