Bi-LSTM electric load prediction method based on deep learning
A forecasting method and deep learning technology, applied in neural learning methods, forecasting, instruments, etc., can solve the problems of low electric load forecasting efficiency, overfitting phenomenon, etc., to reduce overfitting phenomenon, improve adjustment freedom, improve The effect of efficiency
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[0031] The present invention 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, and cannot be used to limit the protection scope of the present invention.
[0032] Table 1 shows the daily electricity load and parameters of an office building in November:
[0033] Table 1
[0034]
[0035]
[0036]
[0037] In a specific case, the first M period parameters of the historical data are obtained, as shown in Table 1, the historical period parameters should not be less than 1, and the parameters include but are not limited to time, temperature, weather conditions (sunny 1, cloudy 0..5, Rainfall (0) area, population, etc. In the embodiment of the present invention, the period parameters are illustrated by taking time, high temperature, low temperature, weather conditions, and load as examples.
[0038] Based on Table 1, if you want t...
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