RETRACTED ARTICLE: Real-time water quality prediction model based on variance statistics and measurement of college students’ physical health

Abstract

In the application of real-time water quality prediction model based on variance statistics and college students’ physical health measurement, when changes are detected, there is almost no possibility that all quality characteristics will change at the same time. In other words, the drift term may only occur in a few elements of the covariance matrix, which leads to sparsity. This paper presents an adaptive lasso multivariable exponentially weighted moving covariance statistical management chart (alewmc) based on sparsity. The pollution of water environment has seriously affected the normal life of human beings, and the real-time water quality prediction model has become the main problem of water environment treatment. In the process of water bloom formation, many uncertain factors are involved, so it is difficult to effectively model and predict the mechanism of real-time water quality prediction model with mathematical methods. In recent years, in the research process of real-time water quality prediction model, many scholars at home and abroad have studied from the mechanism of real-time water quality prediction model and real-time water quality prediction, and have achieved certain research results, which makes real-time water quality prediction become one of the focuses of real-time water quality prediction model. At the same time, for the calculation of college students’ physical health, the development of youth sports has always been highly concerned by the country. How to promote youth sports work, improve young people’s physique, enhance health, and promote the healthy development of young people are the focus of future sports.