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Improving the efficiency of circular irrigation machines based on models of neural network irrigation control

机译:基于神经网络灌溉控制模型提高圆灌机器的效率

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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.
机译:本文介绍了基于神经网络灌溉控制模型的循环灌溉机器运行效率研究的结果。由于高能量强度,现有的灌溉机器不完全能够实现其在灌溉中的优势。仅基于技术流程和关系的物理建模的传统方法通常使得难以找到有效的解决方案。智能灌溉控制对于最大效率和生产率至关重要。提出了一种基于数据挖掘模型的方法,即使用神经控制器控制喷水器。大多数灌溉系统使用开/关控制器。这些控制器不能为不同的时间延迟和不同的系统参数提供最佳结果。基于人工神经网络的建议控制器使用MATLAB创建。主要建模参数是水压和速度。 Neurocontrol,导致可能的实施更好,更有效地管理灌溉机器。

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