Abstract
The article presents the results of studies on the construction of neural network models that will help reduce risks and increase the efficiency of irrigated agriculture. The projected increase in food production on irrigated land is subject to significant risks of climatic and infrastructural nature. Irrigated agriculture, in the global understanding of interrelationships, is a complex dynamic system with nonlinear dependencies. Therefore, traditional approaches based only on physical modeling of environmental and technical processes and relationships often complicate the search for effective solutions. Technological advances that stimulate unprecedented data growth, the rapid extraction of meaningful information from the modern data flow can increase the efficiency of decisions and minimize risks. An approach based on the implementation of neural network models for predicting agro-climatic parameters and intelligent control of irrigation equipment using neurocontrollers is proposed. The models are implemented in the Matlab. The use of these models can significantly reduce risks and increase the efficiency of irrigated agriculture.
Highlights
Agriculture plays a significant role in the global economy due to the global challenges we face
The role of irrigation is increasing, since more than 40% of the growth in world food production and 60% of grain production falls on irrigated lands
According to forecasts, by 2050, the area of irrigated land will increase by 6%, the volume of water withdrawn for irrigation will increase by about 10%
Summary
Agriculture plays a significant role in the global economy due to the global challenges we face. The role of irrigation is increasing, since more than 40% of the growth in world food production and 60% of grain production falls on irrigated lands. According to forecasts, by 2050, the area of irrigated land will increase by 6%, the volume of water withdrawn for irrigation will increase by about 10%. The second important component is the technical equipment of irrigated agriculture, which in many countries is at a rather low level. In this regard, as well as in light of the problem of global climate change, the problem of reducing the risks of irrigated agriculture in general and its individual components in particular is urgent
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