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The Reptile Search Optimization Algorithm, An Efficient And Effective Algorithm In Predicting The Bankruptcy Of Companies
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Mostafa Taghimollaei   , Azar Moslemi * , Abdolkarim Moghaddam |
| Assistant Professor, Department of Accounting, Faculty of Humanities, Khomein Branch, Islamic Azad University, Khomein, Iran, Email: Azar.moslemi.kh@gmail.co |
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Abstract: (389 Views) |
| Predicting the bankruptcy of companies with high accuracy is one of the important issues that helps the continuity of companies. The purpose of this research is to investigate the prediction of corporate bankruptcy using multi-layer perceptron neural network optimized with meta-heuristic algorithms of crawler, whale and swarm search. is particles. The mentioned model has been implemented on the data of 328 examples of listed companies including 246 healthy companies and 82 bankrupt companies in a 6-year period between 2016 and 2021. The criteria for determining the bankruptcy of companies is Article 141 of the Commercial Law. Financial ratios are the independent variables of this research, and the optimal combination of ratios has been extracted using the mentioned algorithms. The performance of the algorithms was evaluated using 5 criteria for evaluating the performance of meta-heuristic algorithms. The results obtained from the simulation and comparison of the proposed algorithms show that the crawler search optimization algorithm compared to the whale optimization algorithms and Particle swarm has performed better in predicting corporate bankruptcy. Also, the results and experiments show that the efficiency and effectiveness of the crawler search optimization algorithm is higher compared to the other two algorithms. |
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| Keywords: Bankruptcy Prediction, Deep Learning, Financial Ratios, Reptile Search Optimization Algorithm |
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Full-Text [PDF 1023 kb]
(113 Downloads)
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Type of Study: Research |
Subject:
Management
Received: 2024/09/23 | Accepted: 2024/12/8 | Published: 2025/10/2
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