传染病传染速度在大区域内的关联建模仿真

Simulation of Affinity Modeling for Infection Speed of Infectious Diseases in Large Area

研究传染病的扩散速度对病情的控制问题。传染病在扩散过程中,受到不同区域中人群组成、环境特征不同的影响,存在高度的非线性与随机性。传统的扩散模型通过高维度约束,扩散随机性较强,设定过多前提条件,导致模型复杂,效果不好。提出基于加权时态关联挖掘算法的传染病传染速度在大区域内的关联建模方法。提取传染病传染速度影响因素,根据上述影响因素,建立加权时态关联模型,计算不同影响因素的支持度,并建立候选项集树,实现传染速度估计。实验结果表明,利用改进算法进行传染病传染速度在大区域内关联建模,能够提高传染病传染速度仿真的真实度,得到精确的估计结果,满足传染病预防和控制的临床需求。

Infection speed of infectious diseases for the disease control is researched. In the process of diffusion, infectious diseases is influenced by the constitution of crowd in different area and the different environmental charac- teristics, there is a highly nonlinear and randomness. In the paper, the affinity modeling of infection speed of infec- tious diseases in large area based on the weighted mining temporal correlation algorithm was proposed. The influenced factors of infection speed of infectious diseases was extracted. According to the above factors, a weighted temporal correlation model was established. A support degree of different influenced factors was calculated, and a candidate i- tem - set tree was established to realize the estimation of the infection speed. Experimental resuhs show that the use of improved algorithm for the affinity modeling of infection speed of infectious diseases in large area, can increase the validity of simulation on the infection speed of infectious disease, obtain accurate estimation results, and meet the clinical needs of prevention and control of infectious diseases.