E3S Web Conf.
Volume 280, 2021Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021)
|Number of page(s)||7|
|Section||Measuring, Forecasting and Monitoring Sustainability|
|Published online||30 June 2021|
Application of fuzzy time series forecasting approach for predicting an enterprise net income level
1 Khmelnytskyi National University, Faculty of Economics and Management, Department of Automated Systems and Modeling in Economics, 11 Instytutska Str., Khmelnytskyi, 29016, Ukraine
2 Gdańsk University of Technology, Faculty of Management and Economics, Department of Informatics in Management, 11/12 Gabriela Narutowicza Str., 80-233 Gdańsk, Poland
3 Vytautas Magnus University, Faculty of Bioeconomy Development, Business and Rural Development Research Institute, 11 Studentu Str., Akademija, LT-52261 Kaunas, Lithuania
4 Iv. Javakhishvili Tbilisi State University, Faculty of Economics and Business, Department of Information Technology in Economics and Business, 1 Chavchavadze Ave., 0107 Tbilisi, Georgia
* Corresponding author: firstname.lastname@example.org
To ensure the sustainable development of an enterprise, it is necessary to properly analyze the enterprise development, to ground the plans and management decisions on effective diagnostics and prediction of current and future economic situation at the enterprise. The article presents a study on the application of fuzzy time series forecasting methods. A new approach is applied to forecasting an enterprise's net income using a fuzzy technique. For testing the methodology, there were used statistical data on the enterprise net income level of the Ukrainian enterprise from 2002 to 2017. In the method of Stevenson and Potter, it is proposed to use as the universe of discourse, in the process of applying the method for all defined fuzzy sets, the intervals of variation of such indicator as growth rate. The same background as in Stevenson and Porter’s model is used in this article for forecasting the time series levels using the growth rates of the actual data as the universe of discourse. The forecasting results, obtained by this approach, are supposed to have more accuracy rate than other fuzzy time series models. Some modifications of this technique are proposed to obtain a higher accuracy rate and a point forecast one step forward.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.