Electricity larceny prevention behavior identification method and system
An identification method and anti-stealing technology, which are applied in neural learning methods, data processing applications, prediction and other directions, can solve the problems such as failure to fully realize automatic alarm, phase failure, power failure, and inability to upload voltage reverse phase sequence in time. Improve work efficiency and narrow the search effect
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[0040] The application will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solutions of the present invention more clearly, but not to limit the protection scope of the present application.
[0041] Such as figure 1 As shown, a kind of anti-stealing behavior identification method of the present invention is characterized in that:
[0042] The method comprises the steps of:
[0043] Step 1: Obtain the user's historical power consumption evaluation index parameter data, including the power consumption, power consumption factor, three-phase voltage unbalance rate, three-item current unbalance rate, meter type and whether it is stolen Electric sign.
[0044] Step 2: Based on the user's historical electricity consumption evaluation index parameter data, build and train a user identification model suspected of stealing electricity, including:
[0045] Step 2.1: Normalize the parameter dat...
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Abstract
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