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In this paper, we investigate the dynamics and optimal control strategies of a modified hand, foot, and mouth disease (HFMD) model incorporating the EV-A71 vaccination in Wenzhou, China, analytically and numerically. We define the basic reproduction number R0 and show that it can be used to determine whether HFMD becomes extinct or not. Based on the monthly reported HFMD cases in Wenzhou for 76 months, we estimate the parameters in the dynamic model by using the method of minimum chi-square fitting, conduct the sensitivity analysis to investigate the influence of each uncertain parameter on R0 with the methods of Latin hypercube sampling and partial rank correlation coefficient, and find that the EV-A71 vaccination does not lead to the extinction of HFMD, but slightly reduces the incidence of HFMD. In order to control the spread of HFMD in Wenzhou, we need to increase the rate of EV-A71 vaccination, decrease the contact rates, and shorten the course of disease.

In order to solve the problem that education departments urgently need intelligent and efficient information technology to deal with massive data, so as to mine valuable information for management decision-making, an overall scheme framework of education informatization is proposed. The framework takes data mining as a tool, combined with the theoretical knowledge of cloud computing, and takes the student data of a school as an example to verify the practicability of the framework system. The results are as follows: the framework clusters the students of a school. The overall level of students in cluster 1 is high, accounting for 45.07% of the total number. These kinds of students have solid basic theory, strong logical thinking ability, and excellent professional knowledge learning. The overall level of students in cluster 2 is average, accounting for 38.03% of the total number. This kind of students should pay attention to the study of professional courses and the cultivation of professional skills. The rest are students in cluster 3. These kinds of students have weak basic professional knowledge and poor thinking and logic ability. Through the accuracy before and after pruning output from the model, the accuracy before pruning is 87.32% and the accuracy after pruning is 97.37%. The noise data are eliminated in the process of pruning. The framework established in this study provides a certain decision-making basis for education and teaching and explains the feasibility and effectiveness of the application of data mining technology in educational informatization.

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