| 线性回归模型精化方法 |
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| 引用本文： | 张志伟,胡伍生,黄晓明. 线性回归模型精化方法[J]. 东南大学学报(自然科学版), 2009, 39(6). DOI: 10.3969/j.issn.1001-0505.2009.06.037 |
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| 作者姓名： | 张志伟 胡伍生 黄晓明 |
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| 作者单位： | 东南大学交通学院,南京,210096 |
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| 基金项目： | 国家高技术研究发展计划(863计划)资助项目 |
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| 摘 要： | 为了解决由试验观测数据建立的回归拟合模型存在的模型误差,用基于回归残差的神经网络方法精化模型.采用给定方程获得模拟数据,通过数据结构散点图建立回归模型趋势项,利用经典最小二乘法估计趋势项参数,由趋势项参数计算回归残差,借助误差分级迭代的改进BP算法对趋势项进行精化,将两部分叠加获得精化模型.试验结果验证了基于回归残差的神经网络方法精化模型的有效性:神经网络方法精化后的模型能提高回归模型的拟合及预测精度5倍以上,优于最小二乘配置法和半参数法精化结果.神经网络方法精化模型既克服了单一神经网络模型的不可解释性,使模型具有物理意义,又具有较高的预测精度.
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| 关 键 词： | 模型精化 趋势项 回归残差 神经网络 |
Linear regressive model improved by neural network |
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| Zhang Zhiwei Hu Wusheng Huang Xiaoming. Linear regressive model improved by neural network[J]. Journal of Southeast University(Natural Science Edition), 2009, 39(6). DOI: 10.3969/j.issn.1001-0505.2009.06.037 |
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| Authors: | Zhang Zhiwei Hu Wusheng Huang Xiaoming |
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| Affiliation: | Zhang Zhiwei Hu Wusheng Huang Xiaoming(School of Transportation,Southeast University,Nanjing 210096,China) |
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| Abstract: | The regression fitting model established with the experiment observation data inevitably has the model error.Thus the neural network method based on the regression residual is adopted to improve the model.The simulation data are obtained by the given equation,and the tendency item of regression model is established by the chart of scatter data structure.The tendency parameter is estimated by the classical least squares method,and the regression residual is computed through the tendency parameter.The error g... |
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| Keywords: | improving model tendency item regressive residual neural network |
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