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

被引:3
|
作者
Li, Na [1 ]
Li, Meng [2 ]
机构
[1] Qinhuangdao Vocat & Tech Coll, Dept Commerce & Trade, Qinhuangdao 066100, Peoples R China
[2] Hebei Inst Int Business & Econ, Qinhuangdao 066311, Peoples R China
关键词
DESIGN;
D O I
10.1155/2022/1487746
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
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页数:10
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