Epidemic prediction based on entropy-improved factor analysis and WOA-optimized BP network algorithm
Jianan Zhang, Duan Hongyi, Tong Bingsong · 2023
The new Coronavirus epidemic has had a huge impact on the economy, politics, and culture worldwide. However, it is very difficult to obtain accurate data on the new crown epidemic due to various uncertainties, such as the difficulty of detection. In this paper, we use objective and real Baidu search indexes as the basic data set and use factor analysis with the improvement of entropy method to reduce the dimensionality of Baidu search index data to solve the problem of fixed parameters caused by its excessive dimensionality. After that, the WOA algorithm is used to optimize the parameters of the conventional BP neural network, thus making the fit and accuracy greatly improved, which is of great practical significance for the prediction of epidemic data.