[1]James A. Ohlson, Financial Ratios and the Probabilistic Prediction of Bankruptcy, Journal of Accounting Research, Vol. 18, No. 1, Spring, 1980, Page 109 of 109-131

[2]Timo Salmi & Teppo Martikainen. (2005). A Review of the Theoretical and Empirical Basis of Financial Ratio Analysis. The Finnish Journal of Business Economics, 4(94), 426-448.

[3]Hui Li , Jie Sun. (2011). Principal component case-based reasoning ensemble for business failure Prediction. Elsevier Journal of Information & Management, 48, pp. 220–227.

[4]Philippe du Jardin. (2010). Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy. Elsevier Journal of Neurocomputing, 73, pp. 2047–2060.

[5]Martin.A, D.Maladhy, V.Prasanna Venkatesan, A framework for business intelligence application using ontological classification, International Journal of Engineering Science and Technology, Vol. 3 No. 2 (2011a), pp. 1213-1221.

[6]Martin.A, M. Manjula and Dr. V.Prasanna Venkatesan, A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm, IJCSI International Journal of Computer Science Issues ISSN (Online): 1694-0814. Impact Factor – 0.242, Vol. 8, Issue 3, No. 2, May 2011

[7]Martin.A, V. Prasanna Venkatesan, “To find most impact financial features on bankruptcy models using Genetic Algorithm”, Proceedings of International conference on Advances in Engineering and Technology [ICAET-2011]. ISBN 978-1-4507-6433-9, E.G.S. Pillay Engineering College, Nagapattinma, India, 27-28, May, 2011

[8]A. Martin, V. Gayathri, G. Saranya, P. Gayathri, Dr. V. Prasanna Venkatesan, A hybrid model for bankruptcy Prediction using genetic Algorithm, fuzzy c-means and mars, International Journal on Soft Computing ( IJSC ) ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print], Vol.2, No.1, February 2011

[9]A. Martin, J. Madhusudhnan, T. Miranda Lakshmi, V. Prasanna Venkatesan, To Find Best Bankruptcy Model using Genetic Algorithm, CiiT International Journal of Artificial Intelligent Systems and Machine Learning Print: ISSN 0974 – 9667 & Online: ISSN 0974 – 9543, Impact Factor – 0.765, Vol. 8, Issue 1,2011

[10]Martin. A, T. Miranda Lakshmi, V. Prasanna Venkatesan, “A Business Intelligence Framework for Business Performance using Data Mining Techniques”, IEEE International Conference on Emerging Trends in Science, Engineering, & Technology (INCOSET”, 2012), J.J. College of Engineering and Technology, Tiruchirappalli, India, 13-14, Dec, 2012

[11]Martin.A,T. Miranda Lakhmi, Dr.V. Prasanna Venkadesan, “An Analysis on Business Intelligence Models to Improve Business Performance”, Proceedings of IEEE International Conference on Advances in Engineering, Science and Management – [ICAESM 2012]. ISBN 978-81-909042-2-3, E.G.S. Pillay Engineering College, Nagapattinma, India, 30 & 31, March 2012

[12]Martin,T. Miranda Lakshmi, Dr. V. Prasanna Venkatesan, “A Study on Business Intelligence Models to Identify the BI Model for Business Performance”, Proceedings of National Conference on National Conference on Information Technology (NCIT - 2012), Dept. of IT, Pondicherry Engineering College, Puducherry, 15, Feb,2012e

[13]A. Martin, V. Aswathy, S. Balaji and V. Prasanna Venkatesan, An Analysis on Qualitative Bankruptcy Models to Frame Bankruptcy Prediction Rules using Ant Colony Algorithm, CiiT International Journal of Automation and Autonomous Systems ISSN 0974-9659, Impact Factor – 0.501, Vol.3, No.8,Oct’ 2011

[14]Martin.A, V.Aswathy, S.Balaji, T. Miranda Lakshmi, Dr.V. Prasanna Venkatesan,” An Analysis on Qualitative Bankruptcy Prediction Using Fuzzy ID3 and Ant Colony Optimization Algorithm”, Proceedings of IEEE International conference on Pattern Recognition, Informatics and Medical Engineering [PRIME 2012]. ISBN:978-1-4673-1037-6, Periyar University, Salem, Tamilnadu, India, 21–23, March 2012

[15]Martin.A, S. Balaji, V. Prasanna Venkatesan, Effective Prediction of Bankruptcy based on the Qualitative factors using FID3 Algorithm, International Journal of Computer Applications. ISSN 0975 – 8887, Impact Factor 0.835, Vol. 43, No. 21, Apr’2012

[16]Martin.A, V. Aswathy, V. Prasanna Venkatesan, Framing Qualitative Bankruptcy Prediction Rules Using Ant Colony Algorithm, International Journal of Computer Applications, ISSN 0975 – 8887, Impact Factor 0.835, Vol. 41, No. 21, Mar’ 2012

[17]Martin.A, R. Kethar sri gowri, V.Aishwarya, A. Abinaya, V.Prasanna Venkatesan, “Survey on Applications of Ant Colony Optimization in Bankruptcy Prediction”, Proceedings of Third National Conference on Computing Concepts in Current Trends (NC4T’12), Dept. of Computer Applications, Sathyabama University, Chennai, 23-24, Aug, 2012

[18]Myoung-Jong Kim, Ingoo Han, The discovery of experts’ decision rules from qualitative bankruptcy data using genetic algorithms, Expert Systems with Applications 25 (2003) 637–646

[19]Hui-Ling Chen, Bo Yang, Gang Wang, Jie Liu, Xin Xu, Su-Jing Wang, Da-You Liu.(2011). A novel bankruptcy prediction model based on an adaptive fuzzy k-nearest neighbour method. Elsevier Journal of Knowledge-Based Systems, 24,1348–1359.

[20]Hui Li, Jie Sun.(2012). Case-based reasoning ensemble for business failure prediction: A computational approach from multiple case representations. Elsevier Journal of Expert Systems with Applications, 39(3), 3298-3310.

[21]Altman EI. (1968). Financial ratios discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23,589–609.

[22]Beaver, W. (1966). Financial Ratios as Predictors of Failure. Empirical Research in Accounting, Supplement to Journal of Accounting Research, 71-111.

[23]Ohlson JA. (1980). Financial ratios and probabilistic prediction of bankruptcy. Journal of Accounting Research, 18,109–31.

[24]West, R C (1985) A factor analytic approach to bank condition. Journal of Banking and Finance, 9, 253—266.

[25]Ravisankar, P., Ravi, V., Bose, I. (2010). Failure prediction of dotcom companies using neural network–genetic programming hybrids. Elsevier Journal of Information Sciences, 180, 1257–1267.

[26]Fengyi Lin, Ching-Chiang Yeh, Meng-Yuan Lee, The use of hybrid manifold learning and support vector machines in the prediction of business failure, Journal Knowledge-Based Systems, Volume 24 Issue 1, February, 2011, Pages 95-101

[27]Arezoo Aghaie, Ali Saeedi, Using Bayesian Networks for Bankruptcy Prediction: Empirical Evidence from Iranian Companies, 2009 International Conference on Information Management and Engineering, pp. 450-455

[28]Martens, David, Fawcett, Tom and Baesens, Bart (2011) Editorial survey: swarm intelligence for data mining. [in special issue: Swarm Intelligence] Machine Learning, 82, (1), 1-42.

[29]K. N. V. D. Sarath Vadlamani Ravi, Association rule mining using binary particle swarm optimization, Journal Engineering Applications of Artificial Intelligence archive Volume 26 Issue 8, September, 2013, Pages 1832-1840

[30]Kasirga Yildirak, Ömür Süer , Kasirga Yildirak, Ömür Süer , The Importance of Qualitative Factors in Firm Default: Evidences from Turkey, CiteSeerX, ULR: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.225.7208 – [Retrieved on 03/September/2013]

[31]Yi-Chung Hu, Bankruptcy prediction using ELECTRE-based single-layer perceptron, Journal of Neuro computing, Volume 72 Issue 13-15, August, 2009, Pages 3150-3157 

[32]Neşe Yalçın Seçme, Ali Bayrakdaroğlu, Cengiz Kahraman, Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS, Expert Systems with Applications, Volume 36, Issue 9, November 2009, Pages 11699–11709

[33]Rafael S. Parpinelli, Heitor S. Lopes, Alex A. Freitas, Data Mining With an Ant Colony Optimization Algorithm, IEEE transactions on evolutionary computing, Vol. 6, No. 4, August 2002.

[34]Rafael S. Parpinelli, Heitor S. Lopes, Alex A. Freitas, An Ant Colony Algorithm for Classification Rule Discovery, Chapter X, Idea Group Publishing, pp.190-208, 2002 

[35]Khodadadi Vali, Abolfazl (Parviz) Zandimia, Nouri Marzieh, Application of Ants Colony System for bankruptcy Prediction of Companies Listed in Theran Stock Exchange, Business Intelligence Journal 01/2010

[36]Neşe Yalçın Seçme, Ali Bayrakdaroğlu, Cengiz Kahraman,Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS, Expert Systems with Applications, Volume 36, Issue 9, November 2009, Pages 11699–11709

[37]Shuihua Wang, Lenan Wu1, Yudong Zhang, Zhengyu Zhou, Ant colony algorithm used for bankruptcy prediction, Information Science and Engineering (ISISE), 2009 Second International Symposium on, Date of Conference: 26-28 Dec. 2009, Page(s):137 - 139 E-ISBN :978-1-4244-6326-8

[38]Bo Liu, Hussein A. Abbass, Bob McKay, Classification Rule Discovery with Ant Colony Optimization, IEEE Computational Intelligence Bulletin, Vol 3, No 1, 2004.

[39]Karthikeyan.T, Mohana Sundaram.J, A Study on Ant Colony Optimization with Association Rule, International Journal of Advanced Research in Computer Science and Software Engineering-ISSN: 2277 128X, Volume 2, Issue 5, May 2012

[40]Allen Chan and Alex Freitas, A New Classification-Rule Pruning Procedure for an Ant Colony Algorithm, Proceeding EA'05 Proceedings of the 7th international conference on Artificial Evolution, Springer-Verlag Berlin, Heidelberg, 2005, Pages 25-36 

[41]Rafael S. Parpinelli, Heitor S. Lopes, Alex A. Freitas, Data Mining with an Ant Colony Optimization Algorithm, 2002, http://sci2s.ugr.es/keel/pdf/algorithm/articulo/Ant-IEEE-TEC.pdf [Retrieved on April, 2013]

[42]P. Ravi Kumar, V. Ravi, Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review, European Journal of Operational Research, Volume 180, Issue 1, 1 July 2007, Pages 1–28

[43]Ervin L. Black, F. Greg Burton and Peter M. Johnson,” Qualitative Factors as Determinants of Continued Success: An Examination of eBusiness Entrepreneurial Firms Using the New Venture Template™”, The Journal of Entrepreneurial Finance Volume 13, Issue 2, ISSN: 1551-9570, 2009.

[44]Tony White, Ant Colony Optimization and the Ant-Miner Algorithm (2006), http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.83.6718 [Retrieved on 05/Sep'/2013].