School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha 410114, China.
Comput Intell Neurosci. 2022 Mar 19;2022:8456197. doi: 10.1155/2022/8456197. eCollection 2022.
With the rapid development of construction projects, more and more engineering corruption problems have emerged. Therefore, this paper proposes a SEIR (susceptible-exposed-infected-recovered) based corruption model to better understand the propagation process of corruption cases in construction projects. In this model, the data samples are collected from the 2018 Engineering Corruption Case Judgment Document, the propagation parameters are obtained through actual case analysis with the help of complex networks, the change process and key influencing factors of actual nodes in engineering corruption cases are simulated by Python. The study results indicate that the personnel conforms to the "4-9 transmission law," in which the early stage is a period of high incidence of corruption cases. The network of corruption cases is somewhat vulnerable, and its spread is about minus 8 times the change in crackdown rate and 10 times the change in infection rate. The variation range of the susceptible population S and the removed person in the propagation simulation curve can predict the relationship between corruption infection rate and crackdown rate, which can provide theoretical guidance for preventing the occurrence of corruption.
随着建设项目的快速发展，越来越多的工程腐败问题已经显现。因此，本文提出了一个基于 SEIR（易感-暴露-感染-恢复）的腐败模型，以更好地理解建设项目中腐败案件的传播过程。在这个模型中，数据样本是从 2018 年的工程腐败案例判决文件中收集的，传播参数是通过借助复杂网络对实际案例进行分析而获得的，Python 被用来模拟工程腐败案例中实际节点的变化过程和关键影响因素。研究结果表明，涉案人员符合“4-9 传播规律”，即早期是腐败案件高发期。腐败案例网络具有一定的脆弱性，其传播速度大约是打击力度变化的负 8 倍，感染率变化的 10 倍。传播模拟曲线中易感人群 S 和去除人员 的变化范围可以预测腐败感染率和打击率之间的关系，这可以为防止腐败的发生提供理论指导。
