The Combination of Internet of Things Technology Based on Probability Model Network and Mass Education

Abstract

With the continuous development of the Internet of things, educational informatization has become a hot spot in the application of education. Internet of things technology, combined with various subject fields of education, can better achieve subject teaching objectives and teaching assistance. In the multimode teaching optimization model, weight distribution is a complex multiobjective decision-making problem. In this paper, a Bayesian network based on probability model is proposed, which is combined with the large entropy criterion to determine the comprehensive weight. The combination of Bayesian network and Bayesian statistics can make full use of the information of domain knowledge and sample data. Bayesian network uses arc to represent the dependence between variables and probability distribution table to represent the strength of dependence. It organically combines prior information with sample knowledge to promote the integration of prior knowledge and data, which is particularly effective when sample data is sparse or difficult to obtain. Bayesian network is used to associate objective attributes and influencing factors to self-study the target weight. By grasping the characteristics of information technology and the nature of university citizenship curriculum, this paper further analyzes the internal relationship between them, promotes the deep integration of the two, and improves the effectiveness of university citizenship curriculum teaching. By grasping the characteristics of information technology and the nature of the school civics curriculum, we promote a deeper integration of the two. It is my education that is more advanced.