Predicting corporate financial failure using sigmoidal opposition-based arithmetic optimization algorithm
Mohamed Khaldi, Ghaith Manita, Amit Chhabra, Ramzi Guesmi, Tarek Hamrouni
| Year of publication: |
2025
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|---|---|
| Authors: | Khaldi, Mohamed ; Manita, Ghaith ; Chhabra, Amit ; Guesmi, Ramzi ; Hamrouni, Tarek |
| Published in: |
Computational economics. - Dordrecht [u.a.] : Springer Science + Business Media B.V., ISSN 1572-9974, ZDB-ID 1477445-8. - Vol. 66.2025, 1, p. 517-569
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| Subject: | Machine learning | Arithmetic optimization algorithm | Corporate financial failure prediction | Metaheuristics | Opposition-based learning | Prognoseverfahren | Forecasting model | Algorithmus | Algorithm | Insolvenz | Insolvency | Künstliche Intelligenz | Artificial intelligence | Theorie | Theory | Lernprozess | Learning process | Mathematische Optimierung | Mathematical programming | Heuristik | Heuristics |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1007/s10614-024-10716-z [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015590778