| 基于主成分分析和支持向量机的效能评定 |
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| 引用本文： | 高尚,杨静宇. 基于主成分分析和支持向量机的效能评定[J]. 系统工程与电子技术, 2006, 28(6): 889-891 |
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| 作者姓名： | 高尚 杨静宇 |
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| 作者单位： | 1. 江苏科技大学电子信息学院,江苏,镇江,212003;南京理工大学计算机科学与技术学院,江苏,南京,210094
2. 南京理工大学计算机科学与技术学院,江苏,南京,210094 |
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| 摘 要： | 简述了武器系统效能评定的各种方法,并分析了其特点。建立武器系统参数效能模型,首先要挑选特征参数,提出了采有主成分分析方法选择武器的特征参数。利用支持向量机建立了武器系统参数效能模型,通过实例与神经网络法的结果进行了比较,结果表明支持向量机方法比较精确和简单。
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| 关 键 词： | 评定 支持向量机 主成分分析 武器系统效能 神经网络 |
| 文章编号： | 1001-506X(2006)06-0889-03 |
| 修稿时间： | 2005-02-24 |
Assessing the effectiveness based on principal component analysis and support vector machine |
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| GAO Shang,YANG Jing-yu. Assessing the effectiveness based on principal component analysis and support vector machine[J]. System Engineering and Electronics, 2006, 28(6): 889-891 |
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| Authors: | GAO Shang YANG Jing-yu |
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| Abstract: | Several methods for assessing the effectiveness of weapon system are discussed, and their characteristics are analyzed.Establishing the parameters-effectiveness mode of weapon system,the first place is to select the character parameters of weapon system.The character parameters of weapon system are selected based on principal component analysis.A parameters-effectiveness model is established by using support vector machine.The method is illustrated through examples and is compared with the neural network method.The comparing results show that the support vector machine method is more accurate and simple. |
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| Keywords: | assess support vector machine principal component analysis effectiveness of weapon system neural network |
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