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多元非参数回归建模的神经网络方法 被引量:2

Model-Free Regression Modeling in ANN and Its Application
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摘要 本文提出利用种经网络的非线性表示能力进行多元非参数回归分析,并应用此方法分析全国城镇储蓄存款,预测按龄生育率取得了令人满意的结果。 This paper put forward take advantage of the non-linear expressing ability of ANN to analyze a multivariate model-free regressing problem. Applying this method, we analyze saving deposit balance (year-end)and make predict age-order-specific fertility rates. The result is satisfactory.
作者 杨华民 龚跃
出处 《长春光学精密机械学院学报》 1997年第2期51-55,62,共6页 Journal of Changchun Institute of Optics and Fine Mechanics
关键词 神经网络 BP算法 多元非参数回归 建模 Neural networks BP algorithmi Multivariate model-free regression
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  • 1Hashem S and Schmeiser B. Improving model accuracy using optimal linear combinations of trained newral networks. IEEE Transactions on neural networks, 1995, 6(3): 792-794.
  • 2Clemen R T. Combining forecasts: A review and annotated bibliography. International Journal of Forecasting, 1989, 5:559-583.
  • 3Hashem S and Schmeiser B. Approximating a function and its derivatives using MSE-optimal linear combinations of trained feedforward neural networks, in Proceedings of the 1993 World congress on Neural Networks, NEW Jersey, Lawrence Erlbaum Associates, 1993,1 : 17-620.
  • 4Alpaydin E. Multiple networks for function learning, in proceedings of the 1993 IEEE Intermational Conference on Neural Networks, IEEE, Apr. 1993,1:9-14.
  • 5杨华民,姜会林,龚跃,刘炯,李平.基于神经网络的多种文字识别系统的集成方法[J].兵工学报,1998,19(4):339-343. 被引量:1
  • 6朱勇,谭铁牛,王蕴红.基于笔迹的身份鉴别[J].自动化学报,2001,27(2):229-234. 被引量:34

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