Construction and prediction of regional financial development index based on RBF and SVM integrated learning
Zhao Gaoxiang, Dongchen Wu, Changquan Hu · 2022
With the effective control of the new crown epidemic, how to develop China's financial industry in the post-epidemic era still lacks a suitable regional index system. Taking Beijing, where the financial economy occupies an important position, as an example, this paper selects 12 typical relevant indicators from the four dimensions of structure, scale, vitality and efficiency, and constructs a model based on Radial Basis Function (RBF) and Support Vector Machine (SVM). The threelevel Bagging integrated learning area financial development index system. First, the coefficient of variation method (CVM) is used to determine the weight of each index to measure the level of financial development, and then based on RBF and SVM, the Bagging integrated learning prediction is performed, and the financial development index is obtained. The results show that the RBF-SVM integrated model is more fitting than the single RBF or SVM. The financial development index of Beijing has generally shown positive growth in the past 20 years, and the financial industry has a good development trend. In this paper, we establish a financial development index system to judge regional financial development differences and predict the development trend of the financial industry, thus providing suggestions for the healthy development of my country's financial industry.