Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)
Published: Jan. 1, 2024
Abstract The handling of every major public health event is a test risk early warning ability and national governance capacity will form experience lessons in social governance. In this paper, we use the improved Apriori algorithm to mine classification emergencies, construct emergency response indicators, carry out feature screening indicator system construction. On basis, selected areas are analyzed using Em prediction model based on Markov chains Bayesian networks. A city as research object, first tested for its performance. By comparing it with RBF ARIMA model, has best accuracy, while lowest accuracy. Then, was used cluster derived risks City A, clustering centers four indices were derived, which 0.202, 0.358, 0.492, 0.644, respectively. Secondly, graded, grades classified into grades: mild, moderate, severe, extra severe. Finally, according level characterization, analysis can be seen that environmental factors plains have greater impact occurrence events.
Language: Английский