Management forecast based on big data fusion DEA and RBF algorithm

Abstract

with the rapid development of information technology, how to use big data for effective analysis has become the focus of various industries. Big data will inevitably bring data noise and data redundancy. The traditional big data preprocessing methods do not take into account the functional relationship between variables, and the commonly used big data modeling tools can not effectively model big data with complex nonlinear relationships. This paper puts forward a prediction method combining DEA and RBF, uses DEA to preprocess big data to select the effective date, then uses RBF to model the data, and compares the prediction accuracy with the original environmental management fund data without pre-processing. The results show that the DEA-RBF method has higher prediction efficiency and better prediction accuracy.