Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction
The aim of this research was to model bankruptcy dependency of Lithuanian enterprises on their financial ratios and its dynamics over time by the integration of artificial neural networks and fuzzy logic technology using Adaptive Network – based Fuzzy Inference System (ANFIS). We used data from fina...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Vilnius University Press
2008-01-01
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| Series: | Nonlinear Analysis |
| Subjects: | |
| Online Access: | http://www.journals.vu.lt/nonlinear-analysis/article/view/14589 |
| _version_ | 1811311313614274560 |
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| author | O. Purvinis R. Virbickaitė P. Šukys |
| author_facet | O. Purvinis R. Virbickaitė P. Šukys |
| author_sort | O. Purvinis |
| collection | DOAJ |
| description | The aim of this research was to model bankruptcy dependency of Lithuanian enterprises on their financial ratios and its dynamics over time by the integration of artificial neural networks and fuzzy logic technology using Adaptive Network – based Fuzzy Inference System (ANFIS). We used data from financial reports for three years’ of 230 Lithuanian going and failed enterprises. Input variables used for the ANFIS model training and testing composed of 13 financial ratios of the last year before bankruptcy and 13 variables characterizing changes of that ratios over time. It was checked 1716 subsets of input variables, each subset containing five input variables. This way the ANFIS model and the best subset of predictive variables with minimal training errors was found. Test of that model showed that percentage of right failure and success predictions reached 80 %. Fuzzy rules of the ANFIS were used to construct interpretable rules base, which can be useful for enterprise managers as knowledge for the linguistic diagnosis of failure or financial problems. |
| first_indexed | 2024-04-13T10:15:40Z |
| format | Article |
| id | doaj.art-c2255c20bc434b80b4f01820a5db8a9c |
| institution | Directory Open Access Journal |
| issn | 1392-5113 2335-8963 |
| language | English |
| last_indexed | 2024-04-13T10:15:40Z |
| publishDate | 2008-01-01 |
| publisher | Vilnius University Press |
| record_format | Article |
| series | Nonlinear Analysis |
| spelling | doaj.art-c2255c20bc434b80b4f01820a5db8a9c2022-12-22T02:50:44ZengVilnius University PressNonlinear Analysis1392-51132335-89632008-01-0113110.15388/NA.2008.13.1.14589Interpretable Nonlinear Model for Enterprise Bankruptcy PredictionO. Purvinis0R. Virbickaitė1P. Šukys2Kaunas University of Technology, LithuaniaKaunas University of Technology, LithuaniaKaunas University of Technology, LithuaniaThe aim of this research was to model bankruptcy dependency of Lithuanian enterprises on their financial ratios and its dynamics over time by the integration of artificial neural networks and fuzzy logic technology using Adaptive Network – based Fuzzy Inference System (ANFIS). We used data from financial reports for three years’ of 230 Lithuanian going and failed enterprises. Input variables used for the ANFIS model training and testing composed of 13 financial ratios of the last year before bankruptcy and 13 variables characterizing changes of that ratios over time. It was checked 1716 subsets of input variables, each subset containing five input variables. This way the ANFIS model and the best subset of predictive variables with minimal training errors was found. Test of that model showed that percentage of right failure and success predictions reached 80 %. Fuzzy rules of the ANFIS were used to construct interpretable rules base, which can be useful for enterprise managers as knowledge for the linguistic diagnosis of failure or financial problems.http://www.journals.vu.lt/nonlinear-analysis/article/view/14589bankruptcypredictionANFISknowledge |
| spellingShingle | O. Purvinis R. Virbickaitė P. Šukys Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction Nonlinear Analysis bankruptcy prediction ANFIS knowledge |
| title | Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction |
| title_full | Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction |
| title_fullStr | Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction |
| title_full_unstemmed | Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction |
| title_short | Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction |
| title_sort | interpretable nonlinear model for enterprise bankruptcy prediction |
| topic | bankruptcy prediction ANFIS knowledge |
| url | http://www.journals.vu.lt/nonlinear-analysis/article/view/14589 |
| work_keys_str_mv | AT opurvinis interpretablenonlinearmodelforenterprisebankruptcyprediction AT rvirbickaite interpretablenonlinearmodelforenterprisebankruptcyprediction AT psukys interpretablenonlinearmodelforenterprisebankruptcyprediction |