计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
16期
67-71
,共5页
网络流量%预测模型%相空间重构%支持向量机%粒子群算法
網絡流量%預測模型%相空間重構%支持嚮量機%粒子群算法
망락류량%예측모형%상공간중구%지지향량궤%입자군산법
network traffic%prediction model%phase space reconstruction%support vector machine%particle swarm optimi-zation algorithm
针对网络流量非线性、突变性和混沌性特点，利用相空间重构和支持向量机参数的天然联系，提出一种相空间重构和支持向量机相融合的网络流量预测方法。将网络流量预测精度作为建模目标，采用粒子群算法对空间重构和支持向量机参数进行组合优化，建立最优网络流量预测模型。仿真实验结果表明，相对于传统网络流量预测方法，该方法更加能够刻画网络流量复杂的变化特点，有效提高了网络流量的预测精度。
針對網絡流量非線性、突變性和混沌性特點，利用相空間重構和支持嚮量機參數的天然聯繫，提齣一種相空間重構和支持嚮量機相融閤的網絡流量預測方法。將網絡流量預測精度作為建模目標，採用粒子群算法對空間重構和支持嚮量機參數進行組閤優化，建立最優網絡流量預測模型。倣真實驗結果錶明，相對于傳統網絡流量預測方法，該方法更加能夠刻畫網絡流量複雜的變化特點，有效提高瞭網絡流量的預測精度。
침대망락류량비선성、돌변성화혼돈성특점，이용상공간중구화지지향량궤삼수적천연련계，제출일충상공간중구화지지향량궤상융합적망락류량예측방법。장망락류량예측정도작위건모목표，채용입자군산법대공간중구화지지향량궤삼수진행조합우화，건립최우망락류량예측모형。방진실험결과표명，상대우전통망락류량예측방법，해방법경가능구각화망락류량복잡적변화특점，유효제고료망락류량적예측정도。
The network traffic has nonlinear, mutation and chaos characteristics, so this paper puts forward a network traffic prediction method based on phase space reconstruction and support vector machine using the relation between phase space reconstruction and support vector machine parameters. The network traffic prediction accuracy is taken as the modeling object, and particle swarm optimization algorithm is used to optimize for spatial reconstruction and parameters of support vector machine to establish the optimal network traffic prediction model. The simulation results show that this proposed method can describe network traffic characteristics of complex changes better compared with the traditional network traffic forecast method, and it effectively improve the prediction accuracy of network traffic.
