加权马尔可夫链在传染病发病情况预测分析中的应用

首先基于传染病的发病情况存在大量不确定性的特点,应用有序聚类的方法建立发病人数状态的分级标准;然后针对发病人数序列为相依随机变量的特点,采取以规范化的各阶自相关系数为权重,用加权的马尔可夫链模型来预测和分析发病人数的变化状况,使预测结论的长期效果趋于最优;最后通过实例检验,对预测结果和方法进行评价和深入的分析.

The Application of Weighted Markov Chain on Forecasting in Incidence of Infectious Disease

This paper firstly applied sequential cluster method to set up the classification standard of infectious disease incidence state based on the fact that there are much uncertainty characteristics in the incidence course; then this paper presented a method which is called the weighted Markov chain to predicted the future incidence state by regarding the standardized self-coeffiicients as weights based on the special characteristics of infectious disease incidence being a dependent stochastic variable, and maked the long-term benefit of decision optimal, Finally, testing goodness-of-fit is given to vestify the practicability and reliability of the model and its result by examples.