Network reconfiguration using genetic algorithm-based predictive models
AssigneeAT&T Intellectual Property I, L.P.
InventorGregory E. Feldkamp
Life of this patent
Estimating the term…
Abstract
An example method may include a processing system including at least one processor determining a final weight set comprising weight factors to apply to each of a plurality of performance indicators for a predictive model associated with a target performance indicator using a genetic algorithm. The method may further include the processing system gathering a first plurality of measurements of the plurality of performance indicators for at least a portion of a cellular network, applying the predictive model to the first plurality of measurements of the plurality of performance indicators to generate a prediction for the target performance indicator, and adjusting at least one aspect of the cellular network in response to the prediction.
Claims20
A method comprising:
- determining, by a processing system including at least one processor, a final weight set comprising weight factors to apply to each of a plurality of performance indicators for a predictive model associated with a target performance indicator, wherein the final weight set is selected from among a plurality of candidate weight sets using a genetic algorithm, and wherein the plurality of candidate weight sets comprises weight set pairs selected from an immediately previous generation of candidate weight sets, wherein each weight set pair of the weight set pairs is selected from the immediately previous generation of candidate weight sets probabilistically based upon fitness parameters of the immediately previous generation of candidate weight sets;
- gathering, by the processing system, a first plurality of measurements of the plurality of performance indicators for at least a portion of a cellular network;
- applying, by the processing system, the predictive model to the first plurality of measurements of the plurality of performance indicators to generate a prediction for the target performance indicator;
- and
- adjusting, by the processing system, at least one aspect of the cellular network in response to the prediction.
A device comprising:
- a processing system including at least one processor;
- and
- a computer-readable medium storing instructions which, when executed by the processing system, cause the processing system to perform operations, the operations comprising:
- determining a final weight set comprising weight factors to apply to each of a plurality of performance indicators for a predictive model associated with a target performance indicator, wherein the final weight set is selected from among a plurality of candidate weight sets using a genetic algorithm, and wherein the plurality of candidate weight sets comprises weight set pairs selected from an immediately previous generation of candidate weight sets, wherein each weight set pair of the weight set pairs is selected from the immediately previous generation of candidate weight sets probabilistically based upon fitness parameters of the immediately previous generation of candidate weight sets;
- gathering a first plurality of measurements of the plurality of performance indicators for at least a portion of a cellular network;
- applying the predictive model to the first plurality of measurements of the plurality of performance indicators to generate a prediction for the target performance indicator;
- and
- adjusting at least one aspect of the cellular network in response to the prediction.
A non-transitory computer-readable medium storing instructions which, when executed by a processing system including at least one processor, cause the processing system to perform operations, the operations comprising:
- determining a final weight set comprising weight factors to apply to each of a plurality of performance indicators for a predictive model associated with a target performance indicator, wherein the final weight set is selected from among a plurality of candidate weight sets using a genetic algorithm, and wherein the plurality of candidate weight sets comprises weight set pairs selected from an immediately previous generation of candidate weight sets, wherein each weight set pair of the weight set pairs is selected from the immediately previous generation of candidate weight sets probabilistically based upon fitness parameters of the immediately previous generation of candidate weight sets;
- gathering a first plurality of measurements of the plurality of performance indicators for at least a portion of a cellular network;
- applying the predictive model to the first plurality of measurements of the plurality of performance indicators to generate a prediction for the target performance indicator;
- and
- adjusting at least one aspect of the cellular network in response to the prediction.
Dependencies are inferred from the claim text.