Gavrilovskaya N.V.  

Mathematical modeling of agrometeorological factors to inform models of the productivity of crops

The report considered an actual scientific challenge was to develop a simulation algorithm agrometeorological factors to inform models of the productivity of crops, based on the principle of similarity. In solving the problem of forecasting crop yield with the use of mathematical models of the productivity problem assessing agrometeorological parameters on the date of the forecast until the end of the growing season. The solution to this problem is based on the use of imaging technologies implementations weather scenarios with years of analog and weather data generator.
The intellectual core of this algorithm is determining the technology-age counterparts, which is original and has the scientific and practical importance. The theoretical significance of the research, defined by the possibility of applying the principle of similarity to the tasks of forecasting and agro-meteorological factors, assessing the yield of grain crops. The practical significance is to develop mathematical models and algorithms for agrometeorological information in different types of uncertainties. This contributes to further development and application of mathematical modeling and information technologies to establish quantitative relationships of yield formation of agro-meteorological factors, as well as in the field of predictive forecasting of grain crop yields.

Abstracts file: Тезисы_Гавриловская.pdf

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