Heidary, Mehdi, Ziari, Shokrollah, Shayannia, Seyyed Ahmad, Rashidi Komijan, Alireza. (1404). Financial bankruptcy prediction using artificial neural network and Firefly algorithms in companies listed in Tehran Stock Exchange. هنرهای کاربردی, 16(8), 35-50. doi: 10.22075/ijnaa.2024.33406.4975
Mehdi Heidary; Shokrollah Ziari; Seyyed Ahmad Shayannia; Alireza Rashidi Komijan. "Financial bankruptcy prediction using artificial neural network and Firefly algorithms in companies listed in Tehran Stock Exchange". هنرهای کاربردی, 16, 8, 1404, 35-50. doi: 10.22075/ijnaa.2024.33406.4975
Heidary, Mehdi, Ziari, Shokrollah, Shayannia, Seyyed Ahmad, Rashidi Komijan, Alireza. (1404). 'Financial bankruptcy prediction using artificial neural network and Firefly algorithms in companies listed in Tehran Stock Exchange', هنرهای کاربردی, 16(8), pp. 35-50. doi: 10.22075/ijnaa.2024.33406.4975
Heidary, Mehdi, Ziari, Shokrollah, Shayannia, Seyyed Ahmad, Rashidi Komijan, Alireza. Financial bankruptcy prediction using artificial neural network and Firefly algorithms in companies listed in Tehran Stock Exchange. هنرهای کاربردی, 1404; 16(8): 35-50. doi: 10.22075/ijnaa.2024.33406.4975

Financial bankruptcy prediction using artificial neural network and Firefly algorithms in companies listed in Tehran Stock Exchange

International Journal of Nonlinear Analysis and Applications
مقاله 4، دوره 16، شماره 8، آبان 2025، صفحه 35-50    اصل مقاله (1.99 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2024.33406.4975
نویسندگان
Mehdi Heidary1؛ Shokrollah Ziari* 2؛ Seyyed Ahmad Shayannia3؛ Alireza Rashidi Komijan4
1Department of Industrial Management, Firoozkooh branch, Islamic Azad University, Firoozkooh, Iran
2Department of Mathematics, South Tehran Branch, Islamic Azad University, Tehran, Iran
3Department of Industrial Management, Firoozkooh branch, Islamic Azad University, Firoozkooh, Iran
4Department of Industrial Engineering, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
چکیده
By anticipating financial turmoil, it is possible to take the necessary precautions before financial distress occurs by managers and investors. This study compares two algorithms for predicting bankruptcy using an Artificial Neural Network (ANN) and Neural network optimized metaheuristic Firefly Algorithm (FA). To run the test, initial values are first set for the network weights and biases. Then, during optimization, the FA algorithm generates a population of different weights and biases. The conversion function used in the output layer is linear, and a non-linear sigmoid function is selected for the middle layer. To conduct this research, the data of 79 companies listed on TSE from 2012 to 2015 were collected and analyzed statistically by backpropagation neural network and FA algorithms. The results show that FA, compared to ANN predicted the companies’ bankruptcy much better. Also, the FA Algorithm maintains a good correlation between bankrupt and non-bankrupt companies, just like real data.
کلیدواژه‌ها
Financial Bankruptcy؛ backpropagation neural network؛ Firefly Algorithm
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