employee from 01.01.2008 until now
UDK 63 Сельское хозяйство. Лесное хозяйство. Охота. Рыбное хозяйство
The article considers the use of Big Data technology for planning food production in conditions of uncertainty. The use of a large amount of diverse information allows us to solve various classes of problems of forecasting and planning the production and sale of food products. The conceptual scheme of using of big data technology by agricultural producers is given on the example of the Irkutsk region and groups of solved extreme problems with examples are considered. Data sources and users are described. The current Big Data platforms are presented.
Big Data, agriculture, digital technologies, mathematical modeling
1. Boltvina, E.K. Modeli optimizacii zagotovki dikorastuschey produkcii s interval'nymi parametrami / E.K. Boltvina, Ya.M. Ivan'o // Vestnik IrGTU. - 2016. - № 6 (113). - S. 73-81.
2. Polyakov, G.N. State and tendencies of technical support of agriculture of the Irkutsk region / G.N. Polyakov, S.N. Shukhanov // Bulletin of the International Academy of Agricultural Education. -2019. - № 45. - Pp. 52-57.
3. Cifrovaya transformaciya sel'skogo hozyaystva po sozdaniyu oblachnoy mnogofunkcional'noy platformy «Umnyy fermer 4.0» / P.G. Asalhanov, N.V. Bendik, Ya.M. Ivan'o, A.I. Lobycin // Aktual'nye voprosy agrarnoy nauki. - 2019. - № 31. - S. 39-47.
4. Bylina, S.G. Informatizaciya agroprodovol'stvennogo kompleksa i sel'skih territoriy Rossii: vozmozhnosti i ogranicheniya / S.G. Bylina, M.E. Kadomceva, M.N. Osovin. - Saratov, 2018. - 228 s.
5. Integraciya innovacionnyh sistem monitoringa dlya "umnogo" sel'skogo hozyaystva / M.E. Vyguzov, A.A. Gorbacheva, I.A. Nechaev, N.O. Stryzhkov // Znanstvena Misel. - 2020. - № 38-1 (38). - S. 57-60.
6. Suhobokov, A.A. Vliyanie instrumentariya Big Data na razvitie nauchnyh disciplin, svyazannyh s modelirovaniem / A.A. Suhobokov, D.S. Lahvich // Nauka i obrazovanie: nauchnoe izdanie MGTU im. N.E. Baumana. - 2015. - № 3. - S. 207-240.
7. Priya, N. Dynamic programming based resource optimization in agricultural big data for crop yield maximization / N. Priya, G. Geetha // Journal of Computational and Theoretical Nanoscience. - 2017. - T. 14, № 9. - S. 4464-4470.
8. Rosenheim, J.A. Ecoinformatics (Big Data) for agricultural entomology: pitfalls, progress, and promise / J.A. Rosenheim, C. Gratton // Annual Review of Entomology. - 2017. - T. 62. - Pp. 399-417.
9. Asalhanov, P.G. Struktura programmno-apparatnoy platformy i opredelenie tipovyh IT-tehnologiy v otraslyah rastenievodstva i zhivotnovodstva Irkutskoy oblasti / P.G. Asalhanov, N.V. Bendik // Cifrovye tehnologii i sistemy v sel'skom hozyaystve : materialy mezhdunarodnoy nauchno-prakticheskoy konferencii. -Irkutska, 2019. - S. 3-10.
10. Ivano, Ya.M. Management of the agro-industrial enterprise: optimization uncertainty expert assessments / Ya.M. Ivano, P.G. Asalkhanov, N.V. Bendik // 2019 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon-2019). - 2019. - P. 8934788.
11. Ermakov, S.A. Obespechenie bol'shimi dannymi obschego dostupa kak faktor intensifikacii sel'skogo hozyaystva / S.A. Ermakov // Ekonomika: vchera, segodnya, zavtra. - 2017. - T. 7, № 6B. - S. 199-216.
12. Yin, S. Big Data for Modern Industry: Challenges and Trends / S. Yin, O. Kaynak // Proceedings of the IEEE. - 2015. - Vol. 103(2). - Pp. 143-146. - DOI:https://doi.org/10.1109/JPROC.2015.2388958.
