| 基于小波变换和优化的SVM的网络流量预测模型 |
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| 引用本文： | 周晓蕾,王万良,陈伟杰. 基于小波变换和优化的SVM的网络流量预测模型[J]. 计算机应用与软件, 2011, 28(2): 34-36,59 |
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| 作者姓名： | 周晓蕾 王万良 陈伟杰 |
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| 作者单位： | 浙江工业大学信息工程学院,浙江,杭州,310023 |
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| 基金项目： | 国家自然科学基金(60573123) |
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| 摘 要： | 提出一种基于小波变换和优化的SVM的网络流量预测模型(WaOSVM),首先对网络流量进行无抽取小波分解得到小波系数和尺度系数,然后选取适当核函数的SVM分别进行预测,其中SVM的参数用自适应量子粒子群算法(AQPSO)进行优化,最后将各预测结果进行小波重构得到最终预测结果.实验结果表明:优化过的SVM具有较好的泛化能力...
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| 关 键 词： | 流量预测 (α)Trous 小波变换 SVM 参数优化 量子粒子群 |
NETWORK TRAFFIC PREDICTION MODEL BASED ON WAVELET TRANSFORM AND OPTIMISED SUPPORT VECTOR MACHINE |
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| Zhou Xiaolei,Wang Wanliang,Chen Weijie. NETWORK TRAFFIC PREDICTION MODEL BASED ON WAVELET TRANSFORM AND OPTIMISED SUPPORT VECTOR MACHINE[J]. Computer Applications and Software, 2011, 28(2): 34-36,59 |
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| Authors: | Zhou Xiaolei Wang Wanliang Chen Weijie |
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| Affiliation: | Zhou Xiaolei Wang Wanliang Chen Weijie(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,Zhejiang,China) |
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| Abstract: | A new network traffic prediction model based on wavelet transform and optimised support vector machine(WsOSVM) is proposed.First,the network traffic is decomposed by non-decimated wavelet transform to acquire the scaling coefficients and wavelet coefficients,and then they are sent individually to different SVM with suitable kernel function for prediction.The parameters of SVM are optimised by adaptive quantum particle swarm optimisation(AQPSO).At last the predictions are combined into the final result by wa... |
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| Keywords: | SVM |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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