Using artificial intelligence technologies for forecasting business processes.
Keywords:
business process, forecasting, control system, artificial intelligence, neural network.
Abstract
The article is devoted to topical issues of forecasting the company's business processes, which is an effective means of finding ways to optimize the company's activities and minimize the risks that arise at different stages of activity. Today, a modern company needs a system of models that allows you to build a cycle of management and forecasting of business processes with given properties and behavior, taking into account the impact of the external environment. The most promising method of economic forecasting is the means of neural networks. The combination of artificial intelligence tools and analytical software create a fundamental basis for business process management in any field.
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Yu.Yu. Gromov, O.G. Ivanova, V.V. Alekseev and ets. Intelligent information systems and technologies: textbook. Tambov: FGBOU VPO «TSTU», 2013. 244 p.
Ponomarenko V.S., Minukhin S.V., Znakhur S.V. Teoriya I praktika modelyvannya biznes-protsesiv: monohrafiya.Kharkiv: Vyd.KHNEU, 2013. 244 s.
Haynullin R.N., Rahal Ya., Rizaev I.S., Sharnin L.M. Prphnozirovanie biznes-protsessov na ocnove neyronnykh setey. Vestnik Kazanskoho tekhnolohicheskoho universiteta, 2017.T.20. №3. S.121-124.
Hreshilov A.A., Stakun V.A., Stakun A.A. Matematicheskie metody postroeniya prohnozov. Moskva: Izd.dom “Padio I svyaz”, 1997. 112 s.
Heyets V.P., Klebanova T.S., Ivanov V.V. Modeli I metody sotsialno-ekonomichnoho prohnozuvannya. Kharkiv: Vyd. KHDEU, 2003. 422 s.
Khaykin Saymon Neyronnye Seti / per.s anhl. Moskva: Izd. Dom “Vilyams”, 2006.1006 s.
Uossernen F. Neyrokompyutornaya tekhnika: teoriya I praktika / per.s anhl. Kyiv: Vyd.”Svit”, 1992. 204 s.
Tsmots O.I., Marshuk A.A. Prohnozuvannya finansovoho stanu pidpriyemstva za dopomohoyu shuchykh neyronnykh merezh. Naukovyi visnyk NLTU Ukrainy, 2011. Vyp. 21.9. S.347-352.
Yasinska N., Ivchenkova O. Vykorystannya neyronnykh merezh v modelyuvanni finansovykh rezultativ biznes-protsesiv. Aktyalni pytannya teorii I praktiky finansiv. Svit finansiv, 2019. №3(60). S.108-120.
Kurochkina I.P., Kalinin I.I., Mamatova L.A., Shuvalova E.B. Metod neyronnykh setei v modelirovanii finansovykg pokazateley kompanii. Statistika I ekonomika, 2017. Т. 14, № 5. S. 33–41.
Deductor/ Komponenty platform. BaseGroup. Labs. URL: https://basegroup.ru/deductor/components/studio.
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Published
2021-07-01
How to Cite
Yaremko , S., Kuzmina О., & Novitskyi , R. (2021). Using artificial intelligence technologies for forecasting business processes . COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, (43), 230-235. https://doi.org/10.36910/6775-2524-0560-2021-43-38
Section
Computer science and computer engineering
