| 基于粗糙集的RBF神经网络在装备研制费用预测中的应用 |
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| 引用本文： | 孟科,张恒喜,李登科,邱恺.基于粗糙集的RBF神经网络在装备研制费用预测中的应用[J].装备指挥技术学院学报,2006,17(5):14-17. |
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| 作者姓名： | 孟科 张恒喜 李登科 邱恺 |
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| 作者单位： | 1. 空军工程大学,工程学院,陕西,西安,710038;68054部队
2. 空军工程大学,工程学院,陕西,西安,710038 |
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| 基金项目： | 空军工程大学博士论文创新基金（YF20040032） |
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| 摘 要： | 运用粗糙集方法和信息熵概念,按照费用特征参数相对于费用的重要度的大小,对费用特征参数集进行约简,以确定RBF神经网络输入层变量.在此基础上通过对典型样本的学习,建立装备研制费用预测模型.实例结果表明该方法具有较高的预测精度,是可行的、有效的.
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| 关 键 词： | 粗糙集 神经网络 信息熵 费用预测 |
| 文章编号： | 1673-0127（2006）05-0014-04 |
| 收稿时间： | 2004-12-29 |
| 修稿时间： | 2004年12月29 |
RBF Artificial Neural Network Based on Rough Set and Its Application in Equipment Development Cost Estimation |
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| MENG Ke,ZHANG Hengxi,LI DengKe,QIU Kai.RBF Artificial Neural Network Based on Rough Set and Its Application in Equipment Development Cost Estimation[J].Journal of the Academy of Equipment Command & Technology,2006,17(5):14-17. |
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| Authors: | MENG Ke ZHANG Hengxi LI DengKe QIU Kai |
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| Affiliation: | 1. Engineering college, Air Force Engineering University, Xi an Shaanxi 710038, China; 2. 68054 Troops, China |
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| Abstract: | In term of the important degree of the cost feature parameters to the cost, in order to set the input variables of the RBF artificial network, the Rough set approach and the conception of information entropy are employed to reduce the parameters of the cost feature parameter set. The equipment research cost estimation model is constructed by learning from the typical samples. The results show that the approach can enhance the predication accuracy, and be feasible and effective. |
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| Keywords: | Rough set artificial network information entropy cost estimation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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