Irrigation water distribution intelligent control system and method based on generative adversarial network configuration
A technology of intelligent control system and network architecture, applied in the general control system, control/regulation system, biological neural network model, etc., can solve the problem of not being able to fully utilize the overall benefits of the gate group, not using deep learning technology, and not being able to dynamically track water level changes and related gate status, etc., to achieve the optimal effect of water distribution dispatching
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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 solution of the present invention more clearly, but not to limit the protection scope of the present invention.
[0032] Such as figure 1 As shown, the intelligent control system for irrigation and water distribution based on the GAN architecture uses the GAN framework, including the Generative Convolutional Network (GCCN) and the Discriminative Convolutional Network (DCCN).
[0033] GCCN: Input the historical data of the water consumption of each river section, the upstream and downstream water levels of the gates, and the flow through the gates, and output the opening degree of the gates and the water distribution time of the gates. DCCN: It is used to assist and improve the "generation" ability of GCCN, and judge whether the gate opening degree and gate water distribution time output by GCCN are consist...
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Abstract
Description
Claims
Application Information
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