Research on Mathematical Modeling Competition and Ideological and Political Education Based on Analysis and Prediction Algorithm

Abstract

This paper selects the research of mathematical modeling competition and correlation analysis of ideological and political education based on analysis and prediction algorithm, including corresponding analysis algorithm, time series prediction algorithm, bp neural network prediction algorithm, and grey association analysis algorithm. First of all, when the corresponding analysis method is used, based on the extraction of a large number of ideological and political documents, the indicators of the past three years were obtained, and the four indicators of "teacher system, reform and innovation, cultural integration, and student classroom" were clustered to obtain the status quo and development trend of the four indicators. For the prediction of the future ideological and political education, we used the time-series algorithm and the BP neural network algorithm to derive the number of published articles and the development trends in the ideological and political field in the next two years.Using grey correlation analysis, with "mathematical modeling, politics" as the theme, to all relevant literature retrieval, extract representative 100 articles, to all the factors involved in the article clustering, red elements, traditional culture, classroom atmosphere, personal value, national situation five related factors, analyze the influence of grey correlation, get the results from high to low order: red elements 0.611,0.596, traditional culture, classroom atmosphere 0.594, personal value of 0.593, national situation 0.581, are strong influence factors, so as to prove the rationality of the model.