IAS development for industrial economic forecasting
V.R. Iksanov
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Abstract: This article gives all the latest information on the developments of the artificial intelligence (AI) in the food industry. Drawing upon the findings of scientific research, we hereby present our own interpretation of the notion of artificial intelligence. The application of AI technologies is analysed, generalised and systematised. A number of popular neural networks for recipe generation are offered.
Keywords: IAS, microservice architecture, IAS development, forecasting, industrial economics, MAPE, determination coefficient, Tkinter, Pandas
For citation. Iksanov V.R. IAS development for industrial economic forecasting. News of the Kabardino-Balkarian Scientific Center of RAS. 2025. Vol. 27. No. 3. Pp. 88–98. DOI: 10.35330/1991-6639-2025-27-3-88-98
References
- Kitova O.V., Savinova V.M., Iksanov V.R. Comparative analysis of machine learning methods for forecasting industrial indicators of the Russian Federation. Voprosy istorii [Questions of History]. 2022. No. 9-2. Pp. 248–262. DOI: 10.31166/VoprosyIstorii202209Statyi37. (In Russian)
- Kitova O.V., Kolmakov I.B., Penkov I.A. Support vector machine method for forecasting investment indicators. Ekonomika, statistika i informatika. Vestnik UMO [Economics, Statistics and Informatics. Bulletin of UMO]. 2016. No. 4. Pp. 27–30. EDN: WHOQRX. (In Russian)
- Baturin A.S. Time series and forecasting models [Electronic resource]. Access mode: https://4analytics.ru/prognozirovanie/vremennie-ryadi-i-modeli-prognozirovaniya.html (Accessed: 15.03.2025). (In Russian)
- Kitova O.V., Savinova V.M., Dyakonova L.P. System of hybrid forecasting models for situational centers of regional government bodies and their application in education. Vestnik rossiyskogo ekonomicheskogo universiteta imeni G.V. Plekhanova [Bulletin of Plekhanov Russian University of Economics]. 2017. No. 5(95). Pp. 126–134. EDN: ZSPYVB. (In Russian)
- Kitova O.V., Kolmakov I.B., Domozhakov M.V. et al. Hybrid distributed regression and intelligent systems for forecasting indicators of socio-economic development of Russia. Vestnik rossiyskogo ekonomicheskogo universiteta imeni G.V. Plekhanova [Bulletin of Plekhanov Russian University of Economics]. 2017. No. 2(92). Pp. 147–161. EDN: YNTSCD. (In Russian)
- Savinova V.M. The system of econometric models for forecasting socio-economic indicators of the Russian Federation as the basis of the IAS “Horizon”. Modern Economy Success. 2022. No. 2. Pp. 140–147. EDN: ULYEZO
- Baturin A.S. Time series and forecasting models [Electronic resource]. Access mode: https://4analytics.ru/prognozirovanie/vremennie-ryadi-i-modeli-prognozirovaniya.html (Accessed: 11.03.2025). (In Russian)
- Rustamov A.B. Forecast for the future of factors affecting the volume of production by the regional industrial entities in the digital economy. Ekonomika i predprinimatel’stvo [Economy and Entrepreneurship]. 2022. No. 4(141). Pp. 265–272. DOI: 10.34925/EIP.2022.141.4.050. EDN: BQXFDT
- Tovma O.D. Main types of software architecture [Electronic resource]. Access mode: https://www.artofba.com/post/main-types-of-software-architecture-ru (Accessed: 03/15/2025). (In Russian)
Information about the author
Vladislav R. Iksanov, Master, Assistant of the Department of Computer Science, Plekhanov Russian
University of Economics;
115054, Russia, Moscow, 36 Stremyannyy lane;
vlad-iksanov@mail.ru, ORCID: https://orcid.org/0009-0003-7810-3720, SPIN-code: 6750-3298