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针对当前业务量预测方法过于理想化、预测准确度不高等问题,根据现网业务量特征提出了一种基于乘积季节自回归求和移动平均(S-ARIMA)模型的业务量预测方法.依据现网业务量的特征,详细分析了基于S-ARIMA的业务量预测建模的数学过程,经过现网大量业务量数据验证,S-ARIMA模型相比其他模型方法在预测值和置信区间上均具有较好的结果,是一种合理有效的业务量预测方法.
Aiming at the problems that the current traffic forecasting method is too idealized and the forecasting accuracy is not high, a traffic forecasting method based on the product season autoregressive moving average (S-ARIMA) model is proposed based on the traffic characteristics of the existing network. Network traffic characteristics of the S-ARIMA-based traffic prediction modeling in detail the mathematical process, a large number of traffic data validation network, S-ARIMA model compared with other models in the prediction and confidence intervals have The better result is a reasonable and effective method of forecasting business volume.