The widespread application of data mining technology and the rapid development of machine learning techniques provide a simple and efficient method for predicting local fiscal revenue. The current main model for fiscal revenue prediction involves using data mining techniques for reasonable selection and analysis of data, followed by training neural networks to construct prediction models. This paper proposes a fiscal revenue prediction model based on data mining and grey neural networks, selecting 12 influencing factors that affect fiscal revenue. The Adaptive-Lasso method is used for variable...
