Modelling Crop Yield in Agricultural Regions Using Computer Vision Technology
نویسندگان
چکیده
The article examines new methodologies for modelling crop yield in agricultural regions of Russia based on the use remote capabilities to get information field state. proposed approach can be applied develop indicator systems and create methodological platforms models necessary obtain more accurate estimates. In comparison with traditional regression model, this method uses computer vision technology gather additional data. Statistical hypothesis testing confirmed significance satellite photographs fields improving accuracy forecasting models. Traditional econometric tools were compared various neural networks order discover optimal model. tested using data from 100 located municipalities 43 Russian regions, selected proportion volume production region. conducted analysis showed advantage mixed network other (multilayer perceptron convolutional network) conditions uncertainty a large amount data, help Additionally, while environmental factors have different effects yields, they must considered along socio-economic characteristics. types differing table significantly improve interpretation. results used examining monitoring regional municipalities, determining farm resource requirements, as well creating sectoral comprehensive projects programmes development industry.
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ژورنال
عنوان ژورنال: Èkonomika Regiona
سال: 2022
ISSN: ['2411-1406', '2072-6414']
DOI: https://doi.org/10.17059/ekon.reg.2022-2-20