Modern Analysis of Financial Statements: Pharmaceutical companies in Iran

Ehsan Abolfathi, Peyman Taebi


In this paper aims to overcome the problems associated with traditional financial analysis, have studied new methods for financial analysis in the Iran pharmaceutical industry. Methodology: In this regard, single-stage and two-stage DEA has been used. The data has been gathered from financial statements for 2014 and the analysis focused on efficiency. Finally, by pay attention to the second sheet of paper, concluded that DEA single-stage and two-stage complement each other. Results: The results showed that the gabor based unsupervised learning described in the present study was able to produce accurate results in the classification of breast cancer data and the classification rule identified was more acceptable and comprehensible. Conclusion: There is a strong correlation between the two methods, and they don't show the same things so these two methods are complementary. Also not superiority On each other and both should be used with financial ratios. so The results in this research are not in same way with the results saravanan article but But the same with pitchumani research.


Full Text:



Abolfathi, E., Hamidi Zadeh, M. & Abolfathia, M. 2013. Analyzing Financial Statements of Listed Companies in Tehran Stock Exchange with a

Hybrid Model of Data Envelopment Analysis (Dea) and Artificial Neural Network (Ann). MAGNT Research Report 2 (2): 108-117

Angayarkanni, S. & Saravanan, S. 2007. “SOM Based Visualization Technique for Detection of Cancerous Masses in Mammogram”, IEEE.

Atash Pour, H. & Noorbakhsh, M. 2010. Organizations performance evaluation by balanced scores sample, Foolad journal,2. 6-18.

Chavan, M. 2009. The balanced scorecard a new challenge, Journal of management development, 28(5). 393-406.

Christsen, D. 2008.The impact of Balanced Scorecard usage on organization performance, PhD Dissertation.

ehsan Abolfathi, E., Alavi Sadr, M. & Taebi, P.2015. “A hybrid model by utilizing SOM neural network and K-means for clustering: the quality of responsiveness and accountability at the central library of Science and Research University” International Journal of Life Sciences, 9, 7. 87- 94

Shokri Nooshnagh, M. 2008. Performance evaluation by Balanced Scorecard approach, Quality control monthly, 28, 45-54.

Smruti Sourava, M. & Kumar Bhuyan, P. 2009. "Self Organizing Map of Artificial Neural Network for Defining Level of Service Criteria of Urban Streets", B. Seismol. Soc. Am., 90, 525–530.

Sparks, R. 2001. Balanced Scorecard: Putting Strategy into Action, Business and Industry Specialist, 10(5), 1-4.

Toloie- Eshlaghy, A. Alinejad, S. 2011. Classification of Customers’ behavior in Selection of the Restaurant with use of Neural Network . European Journal of Economics, Finance and Administrative Sciences 38 : 105 – 117.

Uttreshwar, A. 2008. Ghatol in article, “Hepatitis B Diagnosis Using Logical Inference and Self-Organizing Map presents analyzed the application of artificial intelligence in conventional hepatitis B diagnosis”, IEEE Comput. Mar.

Yousesefipourjeddi, KH., Alborzi, M. & Radfar, R. 2014. a decision support system for new product specifications selection : Using Fuzzy QFD and Ann . International Journal of Innovative Technology and Research 2.



  • There are currently no refbacks.