报告人：朱霖河（江苏大学）

报告时间：2025年8月22日 15:30-17:00

报告地点：维格堂 319

摘要：Focusing on H1N1 influenza A disease that has shown signs of recovery recently, we construct a new model based on the traditional susceptible-infected-recovered compartment model by adding a more realistic secondary transmission mechanism and discrete network diffusion characteristics. The Markov Monte Carlo algorithm is used for fitting based on real data to obtain a relatively high R-square fitting index, which testes the universality of the model. Turing pattern is applied as a visualization tool to depict the spread patterns of infectious diseases in space and time. Through spatial autocorrelation analysis, it is determined that Erdős-Renyi (ER) network can more truly describe the transmission of H1N1. While exploring the impact of actual measures on the spread process, the connection between the transmission effect of infectious diseases and the size of the network under different path choices is discussed. In addition, the sensitivity analysis of the basic reproduction number is conducted through the partial rank correlation coefficient. It is determined that the parameters that have a significant impact on the basic regeneration number are the natural growth rate and the removal rate of susceptible individuals and infected individuals. Then, combined with the Normalized Serious Prevalent Area index that characterizes the high-density areas of the infected individuals, on the basis of determining the target pattern on ER networks, parameter identification is carried out respectively by using statistical methods and the optimal control theory. Finally, based on the actual H1N1 disease data, Naive Bayes algorithm and convolutional neural network, are selected to train the data and compare the error indicators, which can provide effective data support for the subsequent control and prevention of infectious diseases.

报告人简介：朱霖河，理学博士（力学、控制科学与工程博士后），江苏大学副教授，硕士生导师，美国《数学评论》评论员，2016-2017年美国亚利桑那州立大学访问学者，研究方向主要涉及生物数学与网络动力学及优化控制等，以第一或通讯在Engineering Applications of Artificial Intelligence、Journal of Nonlinear Science、Physica D、PRE、Journal of Mathematical Physics、Bulletin of Mathematical Biology、Mathematical Biosciences、Discrete and Continuous Dynamical Systems等期刊发表SCI论文80余篇，ESI高被引论文5篇、热点论文2篇，主持国家级和省部级科研项目4项、市厅级科研项目3项、校级教改项目3项（重点2项），入选江苏省科协青年科技人才托举工程，获江苏省高等学校自然科学奖二等奖一项。指导学生获第十八届“挑战杯”全国大学生课外科技学术作品竞赛全国二等奖、江苏省特等奖，全国大学生数学建模竞赛和全国研究生数学建模竞赛全国一等奖、二等奖等奖项70余项。

邀请人：杨凌