Botsheken, M. H., Salimi, M. J., Falahatgar Athadjo, S. (2017). Presenting a hybrid method to predict the financial distress of companies listed on the Tehran Stock Exchange. Financial Research, (2), 173-192.
Buachoom, W., Kasemsan, M.L.K. (2011). Business Failure Prediction by Using the Hybrid Technique of GA and ANFIS Based on Financial Ratio: Evident from Listed Companies in the Stock Exchange of Thailand. Journal of Financial Studies and Research, 2011, 499279.
Fakhrhosseini, S. F., Aghaei Meibodi, O. (2018). Prediction and determination of companies with a high probability of bankruptcy listed in Tehran Stock Exchange (different analysis of models). Journal of decision making and research in operations, (1), 3-14.
Hu, Y. C., Tseng, F. M. (2005). Applying backpropagation Neural Networks to Bankruptcy Prediction. Journal of Electronic Business Management, 3(2), 97-103.
Mirbaqarihir, M., Nahidi Amirkhaiz, M., Shekohi Fard, S. (2015). Evaluating the financial stability and explaining the factors affecting the financial stability of the country's banks. Financial and Economic Policy Quarterly, 4(15), 23-42.
Nowruzi Seyed Hosseini, R. (2019). Qualitative research method using data application and theory. Bonyad-e-Tehran: Tarbiat Modares University.
Parker, S., Castillo, N., Garon, T., Levy, R. (2018). Eight Ways to Measure Financial Health. Chicago: Center for Financial Services Innovation.
Portborstani, A., Dadashi, I., Zare Behnmiri, M. J. (2018). Quantification of independent auditors' report using a fuzzy approach and investigating the capability of predicting bankruptcy from quantified reports in comparison to the type of audit report. Knowledge of Accounting and Management Audit, 31, 169-186.
Purvinis, O., Virbickaite, R., Sukys, P. (2008). Interpretable Nonlinear Model for Enterprise Bankruptcy Prediction, Nonlinear Analysis: Modeling and Control, 13(1), 61-70.
Vakilifar, H. R., Pilevari, N., Zeidi, S. (2013). Providing bankruptcy model using ANFIS. Financial Engineering and Securities Management, 18, 17-30