离散动态贝叶斯网络推理的编程计算算法

摘要

The discrete dynamic Bayesian network is a useful tool for modeling and inferring the time series progress, and it has wide modeling application value. But its inference algorithm needs improving. Concerning the shortcomings of the discrete dynamic Bayesian network, such as its inference algorithm is hard to understand, hard to program and running slowly, this paper proposed the most suitable storage data structure of the discrete dynamic Bayesian network, deduced The fast inference algorithm for the discrete dynamic Bayesian network, and verified the inference algorithm for the discrete dynamic Bayesian networks through a sample.%离散动态贝叶斯网络是对时间序列进行建模和推理的重要工具,具有广泛的建模应用价值,但是其推理算法还有待进一步完善.针对构离散动态贝叶斯网络的推理算法难以理解、编程计算难、推理速度慢的问题,给出了实现离散动态贝叶斯推理算法的数椐结构,推导了进行计算机编程计算的推理算法和编程步骤,并通过实例进行了算理验证.