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| 基于支持向量机的武器系统参数费用模型 | |
| 引用本文： | 高尚,杨静宇,吴小俊,韩斌. 基于支持向量机的武器系统参数费用模型[J]. 数学的实践与认识, 2006, 36(9): 8-14 |
| 作者姓名： | 高尚 杨静宇 吴小俊 韩斌 |
| 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系,江苏,南京,210094 2. 南京理工大学计算机科学与技术系,江苏,南京,210094 3. 江苏科技大学电子信息学院,江苏,镇江,212003 |
| 摘 要： | 在武器系统分析中,建立武器参数费用模型时,首先要挑选特征参数,这里采用R ough理论中的知识约简方法选择武器的特征参数;利用支持向量机建立了参数费用模型;给出了实例和解决此问题的支持向量机源程序.通过实例与线性回归法和神经网络法的结果进行了比较,结果表明支持向量机比较精确和简单. |
| 关 键 词： | Rough集 支持向量机 参数费用模型 知识约简 神经网络 |
| 修稿时间： | 2004-08-27 |
Weapon System''''s Parameter-cost Model Based on Support Vector Machine |
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| GAO Shang,YANG Jing-yu,WU Xiao-jun,HAN Bin. Weapon System''''s Parameter-cost Model Based on Support Vector Machine[J]. Mathematics in Practice and Theory, 2006, 36(9): 8-14 | |
| Authors: | GAO Shang YANG Jing-yu WU Xiao-jun HAN Bin |
| Abstract: | In weapon system analysis,the first thing is to select the character parameters of weapon system.The character parameters of weapon system are selected based on reduction of knowledge.A parameter cost model is established by using support vector machine.The method is illustrated through examples,and the source code is given also.The results obtained from support vector machine method are compared with that from linear regression method and neural network method.The comparing results show that the support vector machine method is more accurate and simple than the linear regression method and neural network method. |
| Keywords: | rough set support vector machine parameter cost model reduction of knowledge neural network |
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