THE RISK ANALYSIS OF ENTERPRISES BANKRUPTCY BY CLASSICAL AND FUZZY MODELS
The study touches upon solving existing urgent problem – analysis of bankruptcy risk for Ukrainian industrial enterprises in conditions of uncertainty using classic models proposed by Altman, Davidova-Belikov as well as fuzzy logic approaches proposed by Mamdani, Tsukamoto and Larsen. The purpose o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Igor Sikorsky Kyiv Polytechnic Institute
2015-06-01
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| Series: | Ekonomìčnij Vìsnik Nacìonalʹnogo Tehnìčnogo Unìversitetu Ukraïni "Kiïvsʹkij Polìtehnìčnij Institut" |
| Subjects: | |
| Online Access: | http://ev.fmm.kpi.ua/article/view/44165 |
| Summary: | The study touches upon solving existing urgent problem – analysis of bankruptcy risk for Ukrainian industrial enterprises in conditions of uncertainty using classic models proposed by Altman, Davidova-Belikov as well as fuzzy logic approaches proposed by Mamdani, Tsukamoto and Larsen. The purpose of the work is in development of theory and software for estimating bankruptcy risk for industrial enterprises. The software created should also provide the possibility for effectiveness analysis for estimated forecasts and respective forecasting algorithms that were used for generating the forecasts. The study also presents the results of comparative analysis for the classic and fuzzy logic based techniques of bankruptcy forecasting of industrial enterprises. The comparison is based on studying of the first and second type errors characteristic for the classic and fuzzy forecasts.
Analysis of the results achieved showed that fuzzy logic based approach provides substantially better results than the classic techniques hired.
The paper also provides results of studying the bankruptcy forecasts for a series of successful enterprises and those that are close to bankruptcy.
The program product created “Fuzzy inference techniques for estimation of bankruptcy level for industrial enterprises” is implemented in C# programming language using instrumentation – Microsoft Visual Studio. |
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| ISSN: | 2307-5651 2412-5296 |