Abstract
The use of artificial intelligence systems makes it possible to increase the accuracy of forecasting crop yields in comparison with traditional methods. The purpose of the study is to analyze research in the field of the use of artificial intelligence systems in predicting crop yields. Currently, artificial intelligence systems have been developed and tested to predict the yield of rice, wheat, lettuce, coffee and other agricultural crops. To do this, systems based on neural networks, genetic algorithms, the support vector machine and others are used. The effects of the use of artificial intelligence systems in predicting crop yields are revealed. They consist in improving the quality of the planning process of consumed resources, optimizing acreage, improving the accuracy of forecasting product prices in comparison with traditional methods. Specific recommendations are given on the use of artificial intelligence systems in optimizing grain production under the given constraints.
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