Predictive modeling of energy consumption in a cellular network

A non-transitory computer-readable storage medium for tangibly storing computer program instructions capable of being executed by a computer processor, the computer program instructions defining steps of:

• receiving raw data from a plurality of data sources, the raw data collected while operating a cellular network;
• normalizing the raw data based on a set of logical cell sites (LCSs) in the cellular network to generate per-LCS data;
• generating an example from the per-LCS data, the example associated with a given LCS in the set of LCSs;
• generating a predicted energy consumption value for the given LCS by inputting the example into a predictive model;
• determining that the predicted energy consumption value is higher than an expected energy consumption value associated with the given LCS;
• and
• labeling the given LCS as an outlier.

An apparatus comprising:

• a processor configured to:
• receive raw data from a plurality of data sources, the raw data collected while operating a cellular network;
• normalize the raw data based on a set of logical cell sites (LCSs) in the cellular network to generate per-LCS data;
• generate an example from the per-LCS data, the example associated with a given LCS in the set of LCSs;
• generate a predicted energy consumption value for the given LCS by inputting the example into a predictive model;
• determine that the predicted energy consumption value is higher than an expected energy consumption value associated with the given LCS;
• and
• label the given LCS as an outlier.