Forecast of Chemical Export Trade Based on PSO-BP Neural Network Model

Abstract

With the gradual deepening of China’s reform and opening up, the degree of foreign development has been deepened, and its dependence on foreign trade has increased. The “export-oriented” economic development has achieved results. Export trade is introducing advanced technology and equipment, expanding employment opportunities, and increasing government revenue. The export trade is affected by various domestic and international factors and is a complex nonlinear system. Although the traditional linear prediction method has the advantages of intuitiveness, simplicity, and strong interpretability, it is difficult to deal with the prediction problem of dynamic and complex nonlinear systems. The neural network is a nonlinear dynamic system, with strong nonlinear mapping ability, strong robustness, and fault tolerance. It has unique advanced advantages for solving nonlinear problems and is very suitable for solving nonlinear problems.