A spatiotemporal context aware hierarchical model for corporate bankruptcy prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15353-6.pdf
Reference47 articles.
1. Acharjya D, Rathi R (2021) An extensive study of statistical, rough, and hybridized rough computing in bankruptcy prediction. Multimed Tools Appl, 1–27. https://doi.org/10.1007/s11042-020-10167-2
2. Alam T M, Shaukat K, Mushtaq M, Ali Y, Khushi M, Luo S, Wahab A (2021) Corporate bankruptcy prediction: an approach towards better corporate world. Comput J 64(11):1731–1746
3. Alexandropoulos S-AN, Aridas CK, Kotsiantis SB, Vrahatis MN (2019) A deep dense neural network for bankruptcy prediction. In: International conference on engineering applications of neural networks, pp 435–444. https://doi.org/10.1007/978-3-030-20257-6_37
4. Altman E I (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Finance 23(4):589–609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x
5. Ansari A, Ahmad I S, Bakar A A, Yaakub M R (2020) A hybrid metaheuristic method in training artificial neural network for bankruptcy prediction, vol 8. https://doi.org/10.1109/ACCESS.2020.3026529
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