CPC G06N 20/00 (2019.01) [G06F 17/18 (2013.01)] | 18 Claims |
1. A method for detecting anomalous elements in data comprising:
generating a data series from a plurality of signals received from one or more cable modems operating on a communication network;
detrending the data series to obtain an un-tilted data series;
designating a number of elements within the un-tilted data series as a sliding window;
moving the sliding window in increments across the un-tilted data series;
calculating a median and a standard deviation for the sliding window at each increment;
when the standard deviation for the sliding window at one of the increments is greater than a threshold (SD threshold), identifying anomalous elements within the sliding window;
replacing the anomalous elements with the median of the sliding window to create a modified sliding window at the one increment;
calculating a new median and a new standard deviation for the modified sliding window;
identifying new anomalous elements within the modified sliding window when the new standard deviation is greater than a new SD threshold;
scoring the data series based on a quantity of the new anomalous elements, a magnitude of the new anomalous elements, or both a quantity and a magnitude of the new anomalous elements;
when the score is greater than or equal to a specified number, identifying which of the one or more cable modems from which the data series is obtained is an impaired cable modem; and
transmitting signals to/from the impaired cable modem outside frequencies associated with the new anomalous elements.
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