基于生产函数与BP神经网络模型的GDP预测
Based on the production function and the BP neural network model for prediction of GDP
本文试图引用生产函数概念，将GDP作为与生产要素的关系，利用人工神经网络建立起GDP预测模型，并以浙江省GDP数据对建立的模型进行训练，得出拟合度较好的神经网络对未来宏观经济形势进行预测。在建立宏观经济形势预测模型时，我们利用第t年的就业人数L和资本投入总量K预测t+1年的GDP。最后采用MATLAB编程实现建模和网络训练。
his paper attempts to invoke the concept of production function. To GDP as the relationship between factors of production, there is use of artificial neural network prediction model for the establishment of GDP. And Zhejiang Provincial GDP data model set up for training, come to a better fit for the future of the neural network to predict the macroeconomic situation. Macroeconomic situation in the establishment of prediction models, we use the first t years of employment in the total(L) and capital(K) inputs prediction t+1 years of GDP. Finally we’ll use of MATLAB programming modeling and network training.
陈怡、武利军
经济学自动化技术经济计算技术、计算机技术
生产函数BP神经网络浙江GDPMATLAB仿真
production functionBP neural networkGDP of Zhejiang ProvinceMATLAB simulation
陈怡,武利军.基于生产函数与BP神经网络模型的GDP预测[EB/OL].(2009-02-20)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/200902-1085.点此复制
评论