DETECTING AND PROCESSING ANOMALOUS PARAMETER DATA POINTS BY A MOBILE WIRELESS DATA NETWORK FORECASTING SYSTEM
First Claim
1. A method for rendering, by a computerized mobile wireless data network performance parameter forecasting system, a forecast for a mobile wireless network performance parameter, the method comprising the steps of:
- acquiring, via a communications network infrastructure for the mobile wireless network, a raw data point set containing a series of data point values for the mobile wireless network parameter;
correcting the raw data point set, the correcting comprising the sub-steps of;
performing a first linear regression on the raw data point set to render an initial best fit line,calculating a current series of data point residuals based upon;
a current best fit line, the current best fit line being in a first instance the initial best fit line, anda current series of data point values, the current series of data point values being in a first instance the raw data point set,decomposing the current series of data point residuals into a current set of seasonal data point residual subsets,performing a boxplot analysis on the current set of seasonal data point residual subsets to identify a current set of anomalous data point residuals,correcting the current set of anomalous data point residuals to render a corrected data point residual set, andapplying the corrected data point residual set to the current best fit line to render a current corrected data point set; and
applying the current corrected data point set to a forecast model to render a forecast for the mobile wireless network performance parameter.
1 Assignment
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Accused Products
Abstract
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.
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Citations
20 Claims
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1. A method for rendering, by a computerized mobile wireless data network performance parameter forecasting system, a forecast for a mobile wireless network performance parameter, the method comprising the steps of:
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acquiring, via a communications network infrastructure for the mobile wireless network, a raw data point set containing a series of data point values for the mobile wireless network parameter; correcting the raw data point set, the correcting comprising the sub-steps of; performing a first linear regression on the raw data point set to render an initial best fit line, calculating a current series of data point residuals based upon; a current best fit line, the current best fit line being in a first instance the initial best fit line, and a current series of data point values, the current series of data point values being in a first instance the raw data point set, decomposing the current series of data point residuals into a current set of seasonal data point residual subsets, performing a boxplot analysis on the current set of seasonal data point residual subsets to identify a current set of anomalous data point residuals, correcting the current set of anomalous data point residuals to render a corrected data point residual set, and applying the corrected data point residual set to the current best fit line to render a current corrected data point set; and applying the current corrected data point set to a forecast model to render a forecast for the mobile wireless network performance parameter. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A non-transitory computer-readable medium including computer-executable instructions that, when executed by a computerized mobile wireless data network performance parameter forecasting system, facilitate rendering a forecast for a mobile wireless network performance parameter by performing a method comprising the steps of:
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acquiring, via a communications network infrastructure for the mobile wireless network, a raw data point set containing a series of data point values for the mobile wireless network parameter; correcting the raw data point set, the correcting comprising the sub-steps of; performing a first linear regression on the raw data point set to render an initial best fit line, calculating a current series of data point residuals based upon; a current best fit line, the current best fit line being in a first instance the initial best fit line, and a current series of data point values, the current series of data point values being in a first instance the raw data point set, decomposing the current series of data point residuals into a current set of seasonal data point residual subsets, performing a boxplot analysis on the current set of seasonal data point residual subsets to identify a current set of anomalous data point residuals, correcting the current set of anomalous data point residuals to render a corrected data point residual set, and applying the corrected data point residual set to the current best fit line to render a current corrected data point set; and applying the current corrected data point set to a forecast model to render a forecast for the mobile wireless network performance parameter. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification