{"title":"基于BP神经网络的网络流量预测策略研究","authors":"Yuanyuan Li, Ming Zhang","doi":"10.1109/CISE.2009.5362972","DOIUrl":null,"url":null,"abstract":"resources efficiently. In this study, we propose a network traffic forecasting strategy based on BP neural network (BP-NTF). First, we analyse the characteristics of network traffic and establish traffic forecasting methods based on BP neural network, then modeling and forecasting the time series of network traffic data; Second, we construct three module, namely, data collection, data processing and traffic forecasting; Last, we use the strong memory and the learning ability of BP neural network to shortterm forecast the network traffic .This model can provide a basis for network monitoring and management and has high application value and very wide meaning.","PeriodicalId":135441,"journal":{"name":"2009 International Conference on Computational Intelligence and Software Engineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Research on Network Traffic Forecasting Strategy Based on BP Neural Network\",\"authors\":\"Yuanyuan Li, Ming Zhang\",\"doi\":\"10.1109/CISE.2009.5362972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"resources efficiently. In this study, we propose a network traffic forecasting strategy based on BP neural network (BP-NTF). First, we analyse the characteristics of network traffic and establish traffic forecasting methods based on BP neural network, then modeling and forecasting the time series of network traffic data; Second, we construct three module, namely, data collection, data processing and traffic forecasting; Last, we use the strong memory and the learning ability of BP neural network to shortterm forecast the network traffic .This model can provide a basis for network monitoring and management and has high application value and very wide meaning.\",\"PeriodicalId\":135441,\"journal\":{\"name\":\"2009 International Conference on Computational Intelligence and Software Engineering\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Computational Intelligence and Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISE.2009.5362972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Computational Intelligence and Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISE.2009.5362972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Network Traffic Forecasting Strategy Based on BP Neural Network
resources efficiently. In this study, we propose a network traffic forecasting strategy based on BP neural network (BP-NTF). First, we analyse the characteristics of network traffic and establish traffic forecasting methods based on BP neural network, then modeling and forecasting the time series of network traffic data; Second, we construct three module, namely, data collection, data processing and traffic forecasting; Last, we use the strong memory and the learning ability of BP neural network to shortterm forecast the network traffic .This model can provide a basis for network monitoring and management and has high application value and very wide meaning.