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traffic short term predictions and ARIMA for long- term predictions. [88] IEEE802.11 traffic at the University of North Carolina at Chapel Hill Table 2. Traffic prediction - related works - They evaluate a series of variants of ARIMA, Moving Average (MA) and Exponentially Weighted Moving Average (EMA) methods. They obtain best results for the MA methods. [89] Real traffic traces measured from the GSM network of China Mobile of Tianjin. - They present the results of applying a seasonal ARIMA model with a relative error of 0.02. There is no comparative with other models. Doctoral Thesis: Novel applications of Machine Learning to NTAP - 31PDF Image | Novel applications of Machine Learning to Network Traffic Analysis
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