E3S Web Conf.
Volume 175, 2020XIII International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness – INTERAGROMASH 2020”
|Number of page(s)||10|
|Published online||29 June 2020|
Improving the efficiency of circular irrigation machines based on models of neural network irrigation control
Saratov State Agrarian University, 1, Theatralnaia pl., 410012, Saratov, Russia
* Corresponding author: firstname.lastname@example.org
The article presents the results of studies of the operational efficiency of circular irrigation machines based on models of neural network irrigation control. Existing irrigation machines are not fully able to realize their advantages in irrigation due to the high degree of energy intensity. Traditional approaches based only on physical modeling of technical processes and relationships often make it difficult to find effective solutions. Intelligent irrigation control is essential for maximum efficiency and productivity. An approach based on a model of data mining is proposed, namely, control of a sprinkler using a neurocontroller. Most irrigation systems use ON / OFF controllers. These controllers cannot give optimal results for different time delays and different system parameters. The proposed controller based on an artificial neural network was created using MATLAB. The main modeling parameters are water pressure and speed. Neurocontrol, leads to the possible implementation of better and more effective management of irrigation machines.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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