| 自组织人工神经网络在民航旅客盈利能力细分中的应用 |
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| 引用本文： | 周虹,许俐.自组织人工神经网络在民航旅客盈利能力细分中的应用[J].交通运输工程学报,2003,3(4):78-81. |
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| 作者姓名： | 周虹 许俐 |
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| 作者单位： | 南京航空航天大学,民航学院,江苏,南京,210016 |
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| 摘 要： | 目前采用的基于里程的旅客划分方法不能清晰区分旅客价值，应用Kohonen T自组织特征映射的人工神经网络模型将反映旅客盈利能力的多维行为特征属性数据以有序的方式映射到对旅客盈利性判别等级的低维空间，形成对旅客正确识别的一种拓扑意义的有序图。试验结果表明，此模型对客户细分识别成功率较高，准确率可达90．8％。
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| 关 键 词： | 民航运输 客户细分 人工神经网络 Kohonen T自组织模型 |
| 文章编号： | 1671-1637(2003)04-0078-04 |
| 修稿时间： | 2003年3月21日 |
Application of artificial neural network in airline customer segmentation |
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| ZHOU Hong,XU Li.Application of artificial neural network in airline customer segmentation[J].Journal of Traffic and Transportation Engineering,2003,3(4):78-81. |
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| Authors: | ZHOU Hong XU Li |
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| Abstract: | The segmentation of airlines passengers based on mileage can not reflect passengers characteristics. The model that can show passengers value was developed. In this model an artificial neural network was applied to give a topological maps, with the maps, the data that can indicate passengers value was collected. An example proves that the accuracy to seperate passengers by their value with this model is 90. 8%. 3 tabs, 4 figs, 8 refs. |
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| Keywords: | civil aviation transportation passengers'segmentation artificial neural network Kohonen T self-organizing model |
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