DETECTING AND PROCESSING ANOMALOUS PARAMETER DATA POINTS BY A MOBILE WIRELESS DATA NETWORK FORECASTING SYSTEM

摘要

A computer-automated method is described for identifying and remediating anomalous data points for acquired performance parameter (e.g., KPI) values for components of a mobile wireless data network—such as PDSNs. The remediated data point sets is thereafter used as input to a forecasting model rendering a forecast for a mobile wireless network performance indicator/parameter. Data point sequence seasonality is exploited to improve the detection of anomalous data points. Furthermore, correcting data point sets is reiterated until changes between two iterations of the correction process are within a threshold magnitude for terminating the iterative data point sequence correction process.