计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
15期
84-87,91
,共5页
网络流量%包容性检验%支持向量机%组合预测
網絡流量%包容性檢驗%支持嚮量機%組閤預測
망락류량%포용성검험%지지향량궤%조합예측
network traffic%encompassing test%Support Vector Machine(SVM)%combination forecast
模型选择对网络流量组合预测结果至关重要，为了提高网络流量的预测效果，提出一种包容性检验和支持向量机相融合的网络流量预测模型（ET-SVM）。采用多个单一模型对网络流量进行预测，根据预测结果的均方根误差对模型优劣进行排序，通过包容性检验，根据t统计量检验选择最合适的单一模型，采用支持向量机对单一模型预测结果进行组合得到最终预测结果，通过仿真实验对模型性能进行测试。仿真结果表明，ET-SVM降低了网络流量的预测误差，预测精度得到了提高。
模型選擇對網絡流量組閤預測結果至關重要，為瞭提高網絡流量的預測效果，提齣一種包容性檢驗和支持嚮量機相融閤的網絡流量預測模型（ET-SVM）。採用多箇單一模型對網絡流量進行預測，根據預測結果的均方根誤差對模型優劣進行排序，通過包容性檢驗，根據t統計量檢驗選擇最閤適的單一模型，採用支持嚮量機對單一模型預測結果進行組閤得到最終預測結果，通過倣真實驗對模型性能進行測試。倣真結果錶明，ET-SVM降低瞭網絡流量的預測誤差，預測精度得到瞭提高。
모형선택대망락류량조합예측결과지관중요，위료제고망락류량적예측효과，제출일충포용성검험화지지향량궤상융합적망락류량예측모형（ET-SVM）。채용다개단일모형대망락류량진행예측，근거예측결과적균방근오차대모형우렬진행배서，통과포용성검험，근거t통계량검험선택최합괄적단일모형，채용지지향량궤대단일모형예측결과진행조합득도최종예측결과，통과방진실험대모형성능진행측시。방진결과표명，ET-SVM강저료망락류량적예측오차，예측정도득도료제고。
Model selection is a key problem for combination model of network traffic, and in order to improve the forecasting accuracy of network traffic, this paper proposes a network flow combination model based on encompassing test and Support Vector Machine. A lot of single models are used to forecast the network traffic, and the merits of the model are defined by mean square error of the forecasting results, and then the appropriate single model is selected by encompassing test, and the single model prediction results are combined by Support Vector Machine to get the final forecasting result of network traffic, and the performance of model is tested by the simulation experiment. The simulation results show that the proposed model can reduce the forecasting error and has improved the forecasting accuracy of network traffic.
