基于云计算和极限学习机的网络流量预测研究  

Study on Network Flow Forecast Based on Cloud Computing and Extreme Learning Machine

作　　者：王柯[1] WANG Ke(Hunan Urban Construction College,Xiangtan 411101,China)

机构地区：[1]湖南城建职业技术学院,湖南湘潭411101

出　　处：《山东农业大学学报（自然科学版）》2018年第4期632-635,共4页Journal of Shandong Agricultural University：Natural Science Edition

摘　　要：由于网络数据的复杂性和不确定性,传统的方法存在一定局限性,存在预测误差大和预测存在滞后性的问题,针对网络流量数据,本文将云计算和极限学习机相结合,提出一种基于云计算和极限学习机的网络流量预测方法。研究结果表明,本文方法可以有效提高网络流量预测的精度,为网络流量预测提供新的方法和决策依据。Due to the complexity and uncertainty of network data,the traditional method has certain limitations,there are large prediction errors and delays in forecasting.For network traffic data,this paper combined cloud computing and limit learning machine to propose a network traffic forecasting method based on cloud computing and limit learning machine.The results showed that this method could effectively improve the accuracy of network flow prediction and provide a new method and decision basis for network flow prediction.

关 键 词：云计算 极限学习机 网络流量 神经网络 支持向量机 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]