计算机工程与科学2024，Vol.46Issue(7)：1245-1255,11.DOI:10.3969/j.issn.1007-130X.2024.07.013
基于改进北方苍鹰优化随机配置网络的网络流量预测模型
A network traffic prediction model based on improved northern goshawk optimization for stochastic configuration network
摘要
Abstract
Network traffic prediction,as a critical technology,can assist in achieving rational alloca-tion of network resources,optimizing network performance,and providing efficient network services.With the evolution and development of network environments,the diversity and complexity of network traffic have increased.To improve the accuracy of network traffic prediction,a network traffic predic-tion model based on improved northern goshawk optimization for stochastic configuration network(CNGO-SCN)is proposed.Stochastic configuration network,as a supervised incremental model,has significant advantages in addressing large-scale data regression and prediction problems.However,the accuracy of the stochastic configuration network is influenced by the selection of some hyperparameters.To address this issue,the northern goshawk optimization algorithm is used to optimize the regulariza-tion parameters and scaling factors that affect the performance of the stochastic configuration network,obtaining the optimal values.As the initial distribution of the population in the northern goshawk opti-mization algorithm leads to poor individual quality,chaos logic mapping is introduced to improve the quality of initial solutions.The optimized model is applied to real traffic datasets from the UK academic network,the core network of a European city,and a network collaborative manufacturing cloud plat-form interface established by a cooperative enterprise.It is compared with various neural network mod-els to verify the network traffic prediction capability of the proposed method.Experimental results show that the model has higher prediction accuracy compared to other neural networks,exhibiting superior predictive capability when dealing with complex data in practical scenarios.The prediction error of the model decreases by 0.9%to 99.7%.关键词
网络流量预测/随机配置神经网络/北方苍鹰优化算法/混沌逻辑映射Key words
network traffic prediction/stochastic configuration network/northern goshawk optimiza-tion algorithm/chaotic logic mapping分类
信息技术与安全科学引用本文复制引用
王堃,李少波,何玲,周鹏..基于改进北方苍鹰优化随机配置网络的网络流量预测模型[J].计算机工程与科学,2024,46(7):1245-1255,11.基金项目
国家重点研发计划(2020YFB1713300) （2020YFB1713300）
