| BP神经网络主成分分析法在汽车保有量预测中的应用 |
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| 引用本文： | 何明,过秀成.BP神经网络主成分分析法在汽车保有量预测中的应用[J].交通与计算机,2007,25(4):96-99. |
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| 作者姓名： | 何明 过秀成 |
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| 作者单位： | 东南大学,南京,210096 |
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| 基金项目： | 国家自然科学基金
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江苏省科研项目 |
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| 摘 要： | 针对影响汽车保有量预测的多个因素,采用主成分分析的方法提炼出较少的与线性无关的主要因素,并根据这些因素,利用BP神经网络方法对汽车保有量进行了预测,最后通过实例, 将BP神经网络主成分分析法计算结果和非线性模拟与全要素BP神经网络模拟结果进行比较,得知BP神经网络主成分分析法在运算效率、运算精度上较优.
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| 关 键 词： | 汽车保有量 预测 BP神经网络 主成分分析 神经网络 成分分析法 汽车保有量 预测 应用 Population Automobile Forecasting Principal Component Analysis BP Neural Network 运算精度 运算效率 比较 模拟结果 全要素 线性模拟 计算 网络方法 利用 线性无关 |
| 修稿时间： | 2007-06-10 |
Application of BP Neural Network Principal Component Analysis to Forecasting the Automobile Population |
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| HE Ming,GUO Xiucheng.Application of BP Neural Network Principal Component Analysis to Forecasting the Automobile Population[J].Computer and Communications,2007,25(4):96-99. |
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| Authors: | HE Ming GUO Xiucheng |
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| Institution: | Southeast University, Nanjing 210096, China |
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| Abstract: | With consideration of several factors affecting the automobile population, the method of principal component analysis was used to refine new factors, which were linearly independent. Then, based on these factors, the automobile population was forecast according to principal component by BP neural network simulation. At last, through a case, the result by BP neural network simulation principal component analysis was compared with those by nonlinear simulation and multinomial fitting BP neural network simulation. The conclusion is that the method of BP neural network simulation principal component analysis is superior both in efficiency and precision. |
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| Keywords: | automobile population forecasting BP neural network principal component analysis |
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