Data true value discrimination and deduction method for power communication system based on instable frequency distribution and frequency factor learning
A power communication system and frequency distribution technology, which is applied in the field of truth value discrimination and inference of power communication system data based on unsteady frequency distribution and frequency factor learning, can solve the problems of multi-source heterogeneous big data that do not have applicability and high cost
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[0081] Aiming at the problem of low data quality in the current power communication system, the present invention aims to establish a machine learning discrimination method for automatic distortion identification of power data, distortion bit and truth value reasoning. This method combines all data in the power communication system The format of the unsteady frequency distribution is unified into an unsteady frequency distribution, and then the feature learning is performed through the frequency implicit factor decomposition learning function, so that the unsteady frequency distribution points to the abnormal point in the power communication system, thereby judging the truth of the data.
[0082] For accomplishing the above object, the present invention is divided into four steps as a whole, and the overall flow chart is shown in the attached figure 1
[0083] Step 1 Extract the stable mode of the power dataset
[0084] This step is divided into three sub-steps
[0085] Step...
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