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改进小波包结合支持向量机分类器的无线Ad Hoc网络性能评价

Wireless Ad Hoc netwrok performance evaluation by IWPA and SVMDT
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摘要 使用训练集大小、特征提取方法和识别方法作为影响识别错误率的三个因素,采用改进小波包(IWPA)和SVMDT相结合的方法对无线Ad Hoc网络的性能进行了评价。通过采用方差分析和最小二次无偏估计的方法等数理统计方法分析实验数据,获得了各个因素的主效应及其之间的相互效应对识别错误率边际均值的具体影响程度。研究结果表明,IWPA特征提取方法的性能远优于WPA和WT,SMDT分类方法的性能也优于RBF和SA,并且IWPA和SMDT相结合产生了最佳的交互效应。 Improved wavelet packet analysis and support vector machine were used to evaluate the performance of wireless Ad Hoe network. Experimental results show that the performance of Improved Wavelet Packet Analysis （IWPA） is much better than Wavelet Packet Analysis （WPA） and WT （ wavelet transform）. And the method of SVMDT is superior to RBF SA （simulated annealing）. That IWPA combines SVMDT can get the best effect.
作者 冼广铭 曾碧卿 王先国 唐华 冼广淋
机构地区 华南师范大学计算机工程系 广东轻工职业技术学院计算机系
出处 《计算机应用》 CSCD 北大核心 2009年第1期312-314,共3页 journal of Computer Applications
关键词 改进小波包 SVM决策树 径向基神经网 模拟退火算法 Improved Wavelet Packet Analysis （IWPA） SVM Decision Tree （SVMDT） Radial Basis Function （RBF） Simulated Annealing （SA）
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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2009年 第1期

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