References
- A1 Shalabi, L., and Shaaban, Z., "Normalization as a preprocessing engine for data mining and the approach of preference matrix", IEEE Computer Society, Proceedings of the Internatinal Conference on Dependability of Computer Systems, 0-7695-256, (2006).
- Akdemir, B. and Yu, L., "Elliot waves predicting for stock marketing using Euclidean based normalization method merged with artificial neural network", Fourth International Conference on Computer Science and Convergence Information Technology, (2009), 562-567.
- Barniv, R., Anuragh, A., and Leach R., "Predicting the outcome following bankruptcy filing : a three state classification using NN", International Journal of Intelligence System in Accounting, Finance and Management, Vol.6(1997), 177-194. https://doi.org/10.1002/(SICI)1099-1174(199709)6:3<177::AID-ISAF134>3.0.CO;2-D
- Berry, M. and Linoff, G., "Data mining techniques for marketing, sales and customer support", Wiley Computer Publishing, 1997.
- Chen, W. and Du, Y., "Using neural networks and data mining techniques for the financial distress prediction model", Expert Systems with Applications, Vol.36(2009), 4075-4086. https://doi.org/10.1016/j.eswa.2008.03.020
- Chia, W., Holliday, J., and Willett, P., "Effect of data standardization on chemical clustering and similarity searching", Journal of Chemical Information and Modeling, Vol.49 No.2(2009), 155-161.
- Cror, K., and Ross, A., "Score normalization in multimodal biometric systems", Pattern Recognition, Vol.38(2005), 2270-2285. https://doi.org/10.1016/j.patcog.2005.01.012
- Javanmard, H. and Saleh, F., "The comparison artificial neural networks and multi decimal analysis models for forecasting bankruptcy and financial distress", Proceedings of the Worlds Congress on Engineering, July, 2009.
- Jiang, Y., Wang, Y., and Xu, L., "Using genetic algorithms to predict financial performance", IEEE Xplore, 1-4244-099, (2007), 3255-3229.
- Jolai, F. and Ghanbari, A., "Integrating data transformation techniques with Hopfield neural networks for solving travelling salesman problem", Expert Systems with Applications, Vol.37, No.7(2010), 5331-5335. https://doi.org/10.1016/j.eswa.2010.01.002
- Khashman, A., "Neural networks for credit risk evaluation : Investigation of different neural models and learning schemes", Vol.37, No.9 (2010). 6233-6239 https://doi.org/10.1016/j.eswa.2010.02.101
- Kim, D. "Normalization methods for input and output vectors in back-propagation neural networks", International Journal of Computer Mathematics, Vol.71(1999), 161-171. https://doi.org/10.1080/00207169908804800
- Kim, K. W., Kim, D., and Jung, H. "Normalization methods on back-propagation for the estimation of drivers' route choice", KSCE Journal of Civil Engineering, Vol.9 No.5(2005), 403-406. https://doi.org/10.1007/BF02830631
- Kim, K. and Han, I., "Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index", Expert Systems with Applications, Vol.19(2000), 125-132. https://doi.org/10.1016/S0957-4174(00)00027-0
- Kim, M. and Han, I., "The discovery of experts' decision rules from qualitative bankruptcy data using genetic algorithms", Expert Systems with Applications, Vol.25(2003), 637-646. https://doi.org/10.1016/S0957-4174(03)00102-7
- Kotsiantis, S., Kanellopoulos, D., and Pintelas, P., "Data preprocessing for supervised learning", Internatinal Journal of Computer Science, Vol.1, No.2(2006), 1306-4428.
- Leshno, M., "Neural network prediction analysis: The bankruptcy case", Neural computing, Vol.10, No.2(1996), 125-147.
- Liu, C. and Marukawa, K., "Normalization ensemble for handwritten character recognition", IEEE Computer Society, International Conference on Computational Intelligence for Modeling Control and Automation, 0-7695-218, (2004).
- Mazzatorta,P. and Benfenati, E., "The importance of scaling in data mining for toxicity prediction", Journal of Chemical Information and Computer Sciences, Vol.42(2002), 1250-1255. https://doi.org/10.1021/ci025520n
- Min, S., Lee, J., and Han, I., "Hybrid genetic algorithms and support vector machines for bankruptcy prediction", Expert Systems with Applications, Vol.31(2006), 652-660. https://doi.org/10.1016/j.eswa.2005.09.070
- Mitchel, M., "An introduction to genetic algorithms", Cambridge, MA : The MIT Press, 1996.
- Moody, J. and Utans, J., "Architecture selection strategies for neural networks : Application to bond rating prediction", Neural Networks in the Capital Markets, (1995).
- O'leary, D., "Using neural networks to predict corporate failure", International Journal of Intelligent Systems in Accounting, Finance and Management, Vol.7(1998), 187-197. https://doi.org/10.1002/(SICI)1099-1174(199809)7:3<187::AID-ISAF144>3.0.CO;2-7
- Olden, J. and Jackson, D., "Illuminating the "black box" : a randomization approach for understanding variable contribution in artificial networks", Ecological Modeling, Vol.154, No.1-2(2002), 135-150. https://doi.org/10.1016/S0304-3800(02)00064-9
- Rahimian, E., Singh, S., and Thammachote, T., "Bankruptcy prediction by neural network", Neural Networks in Finance and Investing : Using Artificial Intelligence to Improve Real-World Performance, Probus, Chicage, IL., (1993), 159-176.
- Salchenberger, L., Cinear, E., and Lash, N., "Neural Networks : A new tools for Thrift failure", Decision Science, Vol.23(1992), 899-916. https://doi.org/10.1111/j.1540-5915.1992.tb00425.x
- Schaffer, C. and Green, P., "An empirical comparison of variable standardization methods in cluster analysis", Multivariate Behavioral Research, Vol.31, No.2(1996), 149-167. https://doi.org/10.1207/s15327906mbr3102_1
- Sen, T., Ghandforoush, P., and Stivason, C., "Improving Prediction Of Neural Networks : A Study Of Two Financial Prediction tasks", Journal of Applied Mathematics and Decision Science, Vol.8, No.4(2004), 219-233.
- Shanker, M., Hu, M., and Hung, M., "Effect of data standardization on neural network training", Omega, International Journal of Science, Vol.24 No.4(1996), 385-397.
- Sharda, R. and Wilson, R., "Performance comparison issues in neural network experiments for classification problems", Proceedings of the 26th Hawaii International Conference on System Sciences, IEEE Press, 1993.
- Shin, K. and Han, I., "Case-based reasoning supported by genetic algorithms for corporate bond rating", Expert Systems with Applications, Vol.23, No.3(2002), 321-328. https://doi.org/10.1016/S0957-4174(02)00051-9
- Shin, K. and Lee, T., "A genetic algorithm application in bankruptcy prediction modeling", Expert Systems with Applications, Vol.23, No.3(2002), 321-328 https://doi.org/10.1016/S0957-4174(02)00051-9
- Surkan, A. and Singleton, J., "Neural networks for bond rating improved by multiple hidden layers", International Joint Conference on Neural Networks, (1990), 157-162.
- Swicegood, P., and Clark, J., "Off-site monitoring for predicting bank under performance : a comparison of neural networks, discriminant analysis and professional human judgement", International Journal in Accounting, Finance and Management, Vol.10(2001), 169-186.
- Tam K., "Neural networks models and the prediction of bankruptcy", Omega, Vol.19, No.5(1991), 429-445. https://doi.org/10.1016/0305-0483(91)90060-7
- Tsai, C. and Wu, J., "Using neural network ensembles for bankruptcy prediction and credit scoring", Expert Systems with Applications, Vol.34(2008), 2639-2649. https://doi.org/10.1016/j.eswa.2007.05.019
- Tsukuda, J. and Baba, S., "Predicting Japanese corporate bankruptcy in terms of finance data using neural network", Computer and Industrial Engineering, Vol.1, No.4(1994), 445-448.
- Utans, J. and Moody, J., "Selecting neural network architecture via the prediction risk : Application to corporate bond rating prediction", IEEE Xplore, (1994), 35-41.
- Visalakshi, N. and Thagavel, K., "Impact of normalization in distributed k-means clustering", International Journal of Soft Computing, Vol.4, No.4(2009), 168-172.
- Wang, H. and Zhang, J., "Analysis of different data standardization form for fuzzy clustering evaluation results' influence", IEEE Xplore, 978-1-4244, (2009), 1-4.
- Wilson, R. and Shandra, R., "Bankruptcy prediction using neural networks", Decision Support Systems, Vol.11, No.5(1994), 545-557. https://doi.org/10.1016/0167-9236(94)90024-8
- Wu, C., Tzeng, G., Goo, Y., and Fang, W., "A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy", Expert Systems with Applications, Vol.32, No.2(2007), 397-408. https://doi.org/10.1016/j.eswa.2005.12.008
- Yim, J. and Mitchell, H., "A comparison of corporate failure models in Australia : Hybrid neural networks, logit models and discriminant analysis", RMIT Working Paper, Vol.10(2002).