人群流行病学的空间分布模型仿真研究

Simulation on Spatial Distribution Model of Population Epidemiology

在流行病人群分布模型的研究中,人群流行病学在空间上呈现非周期、几何指数、非线性的特征,分布过程复杂度较高,很难运用单一模型控制。传统的模型仅以小周期模型为基础,对大规模疾病分布建模的过程,以多模型组合逼近完成,缺少约束过程,造成复杂度很高,建模效果不好。为了避免上述缺陷,提出基于约束分类优化算法的人群流行病学空间分布模型。根据约束分类优化相关原理,对流行病的空间分布进行分层约束,得到较为合理的人群流行病种群的分布情况,对流行病种群中的所有个体进行编号处理,通过迭代计算得到最优分布区域的计算结果个体。通过临近地区流行病分布比例,得到人群流行病学的空间位置分布情况。实验结果表明,利用改进算法进行人群流行病学空间分布,能够极大的提高分布建模的准确性,降低建模复杂度。

An optimization algorithm based on constraint classification epidemiological distribution model is presented. According to the related principle of constraint classification optimization, the spatial distribution of the epidemic is constrained by multi - layers, distribution of reasonable crowd epidemic is obtained, the serial number of the epidemic in all the individuals is set up, and the optimal distribution is obtained by iterative calculation results. Through neighborhood epidemic distribution proportion, space distribution of the crowd epidemiology is obtained. The experimental results show that the improved algorithm can greatly improve the accuracy of distribution modehng and reduce the complexity of modeling in population epidemiological distribution.