（毕业设计论文）《人工神经网络BP算法在四川省GDP预测中的应用》.doc

PAGE 人工神经网络BP算法在四川省 GDP预测中的应用 作者姓名：XXX 专业班级：数学与应用数学 指导教师：XXX 摘 要 GDP与大家生活息息相关，没有GDP，人们便无法反映一国的贫富状况和人民的平均生活水平，无法确定一国承担的国际义务，享受的优惠待遇。如何准确的测量未来的GDP走势，使其对国家政策的制定起到参考作用,这是大家普遍关注的问题。然而，随着经济的高速发展，影响GDP的因素变得多种多样。GDP预测模型具有很强的非线性, 传统的线性预测模型难以实现对GDP较为准确的预测。然而，实践证明人工神经网络对于建立预测模型十分有效，它能从数据样本中自动学习以前的经验而无需复杂的查询和表述过程，并自动地逼近那些最佳的数据蕴涵的规律。而在预测方面，BP神经网络算法运用最为广泛。 本文以人工神经网络理论为基础，BP神经网络算法为依据，研究GDP的预测。根据四川省1997年到2007年近10年来的GDP数据，建立了神经网络预测模型，通过对1997到2006年的GDP数据分析、学习，对2007年GDP进行预测。首先对输入数据进行预处理，再利用多层前馈神经网络BP算法来研究人工神经网络在GDP预测中的应用问题。利用MATLAB数学软件对模型求解，并将预测结果与传统模型相比较。结果表明，用人工神经网络建立的预测模型在GDP预测方面具有一定的理论与应用价值。 关键词：GDP；人工神经网络；ＢＰ网络；MATLAB The Forecast of Sichuan Province’s GDP Based on ANN BP Methods Abstract: GDP lives with everyone vitally related. It will not be able to reflect the situation of a countrys wealth and the average standard of peoples living, unable to determine a countrys international obligations, enjoy preferential treatment, if there’s no GDP. The issue which common concern is that how to forecast the trend of the future’s GDP accurately and make GDP play a reference role to the formulation of national policies. However, with the economics’ rapidly development, the impact of GDP’s factors has became variety. GDP forecasting model has a strong non-linear, so traditional linear forecasting model of GDP is difficult to achieve more accurate forecasts. However, the Practice has proved that the establishment of artificial neural network prediction model is very effective,it can automatically to study the experience of the past from the data without the complexity search and expression expression;and it can automatically to close to the regulation which from the best data.In the forecast, BP neural network algorithm being used widely. In this paper, take artificial neural network as theory, BP neural network algorithm as basis, to study the forecast of GDP. According to Sichuan Province from 1997 to 2007, nearly 10 years GDP data, build up a neural network prediction model to