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Using artificial intelligence technologies to predict cash flow

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dc.contributor.authorDadteev, K.
dc.contributor.authorShchukin, B.
dc.contributor.authorNemeshaev, S.
dc.contributor.authorДадтеев, Казбек Маирбекович
dc.contributor.authorЩукин, Борис Алексеевич
dc.contributor.authorНемешаев, Сергей Александрович
dc.date.accessioned2024-11-26T13:04:40Z
dc.date.available2024-11-26T13:04:40Z
dc.date.issued2020
dc.description.abstract© 2020 The Authors. Published by Elsevier B.V.Cash flow is one of the most important concepts of financial analysis at the moment. Cash flow forecasting is a key factor in the financial planning of large commercial banks. This paper describes methods of forecasting cash flow volumes using regression model, ARIMA model and MLP neural network model. As the practice has shown the use of classical models (regression and ARIMA) is preferable in the regions that are not subject to sharp economic changes, and MLP has shown greater efficiency in forecasting in large cities and regional centres, i.e. in places with greater economic activity, where the cash flow is affected by a greater number of factors.
dc.format.extentС. 264-268
dc.identifier.citationDadteev, K. Using artificial intelligence technologies to predict cash flow / Dadteev, K., Shchukin, B., Nemeshaev, S. // Procedia Computer Science. - 2020. - 169. - P. 264-268. - 10.1016/j.procs.2020.02.163
dc.identifier.doi10.1016/j.procs.2020.02.163
dc.identifier.urihttps://www.doi.org/10.1016/j.procs.2020.02.163
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85084499084&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/21701
dc.relation.ispartofProcedia Computer Science
dc.titleUsing artificial intelligence technologies to predict cash flow
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume169
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