Support Vector Machine-Based Nonlinear Model and Its Application in Regional Economic Forecasting

Abstract

The regional economic potential is affected by too many entities and large dynamic changes in the economic structure, resulting in large errors in the prediction obtained by the traditional economic potential development prediction method. Therefore, this paper puts forward the regional economic development potential prediction model with the concept of decision domain, solves the nonlinear characteristics of regional economic impact indicators by using the traditional support vector machine, and obtains the economic prediction data. The decision domain method is introduced in the decision-making process to construct the decision domain of training economic-related data sets. The experimental results show that compared with other prediction models, the model proposed in this paper has higher regional economic prediction accuracy, 2% higher than the baseline method, can quickly and accurately predict the potential trend of regional economic development, and has important application value.