{"title":"网络流量时间序列预测的ANFIS方法","authors":"S. Chabaa, A. Zeroual, J. Antari","doi":"10.1109/MMS.2009.5409834","DOIUrl":null,"url":null,"abstract":"In This paper we have applied the adaptive neuro-fuzzy inference system (ANFIS) which is realized by an appropriate combination of fuzzy systems and neural networks for forecasting a set of input and output data of internet traffic time series. Several statistical criteria are applied to provide the effectiveness of this model. The obtained results demonstrate that the ANFIS model present a good precision in the prediction process of internet traffic in terms of statistical indicators. This model fits well real data and provides an effective description of network condition at different times.","PeriodicalId":300247,"journal":{"name":"2009 Mediterrannean Microwave Symposium (MMS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"ANFIS method for forecasting internet traffic time series\",\"authors\":\"S. Chabaa, A. Zeroual, J. Antari\",\"doi\":\"10.1109/MMS.2009.5409834\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In This paper we have applied the adaptive neuro-fuzzy inference system (ANFIS) which is realized by an appropriate combination of fuzzy systems and neural networks for forecasting a set of input and output data of internet traffic time series. Several statistical criteria are applied to provide the effectiveness of this model. The obtained results demonstrate that the ANFIS model present a good precision in the prediction process of internet traffic in terms of statistical indicators. This model fits well real data and provides an effective description of network condition at different times.\",\"PeriodicalId\":300247,\"journal\":{\"name\":\"2009 Mediterrannean Microwave Symposium (MMS)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Mediterrannean Microwave Symposium (MMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMS.2009.5409834\",\"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 Mediterrannean Microwave Symposium (MMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMS.2009.5409834","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ANFIS method for forecasting internet traffic time series
In This paper we have applied the adaptive neuro-fuzzy inference system (ANFIS) which is realized by an appropriate combination of fuzzy systems and neural networks for forecasting a set of input and output data of internet traffic time series. Several statistical criteria are applied to provide the effectiveness of this model. The obtained results demonstrate that the ANFIS model present a good precision in the prediction process of internet traffic in terms of statistical indicators. This model fits well real data and provides an effective description of network condition at different times.