1 |
Ahn, H., Lee, K. and Kim, K.-j. "Global Optimization of Support Vector Machines Using Genetic Algorithms for Bankruptcy Prediction," Lecture Notes in Computer Science, Vol. 4234 (2006), pp. 420-429.
|
2 |
Babu, T.R., Murty, M.N., "Comparison of genetic algorithm based prototype selection schemes. Pattern Recognition," Vol.34, No.2 (2001), pp. 523-525.
DOI
|
3 |
Chatterjee, S. "Vision-based rock-type classification of limestone using multi-class support vector machine," Neurocomputing, Vol.39, No.1 (2013), pp. 14-27.
|
4 |
Chen, L.H., and Hsiao, H.D. "Feature selection to diagnose a business crisis by using a real GA-based support vector machine: An empirical study," Expert Systems with Applications, Vol.35, No.3 (2008), pp. 1145-1155.
DOI
|
5 |
Crammer, K. and Singer, Y. "On the Learnability and Design of Output Codes for Multiclass Problems," Proceedings of the 13th Annual Conference on Computational Learning Theory, Palo Alto, California, USA (2000), pp. 35-46.
|
6 |
Dash, R., and Dash, P. K. "A hybrid stock trading framework integrating technical analysis with machine learning techniques," The Journal of Finance and Data Science, Vol.2 (2016) 42-57.
DOI
|
7 |
Hong, T., and Park, J. "Feature Selection for Multi-Class Support Vector Machines Using an Impurity Measure of Classification Trees:An Application to the Credit Rating of S&P 500 Companies," Asia Pacific Journal of Information Systems, Vol. 21, No. 2(2011), pp. 43-58.
|
8 |
Howley, T., and Madden, M.G. "The Genetic Kernel Support Vector Machine: Description and Evaluation," Artificial Intelligence Review, Vol. 24, Nos. 3-4 (2005), pp. 379-395.
DOI
|
9 |
Hsu, C.W., and Lin, C.J. "A Comparison of Methods for Multiclass Support Vector Machines," IEEE Transactions on Neural Networks, Vol. 13, No. 2 (2002), pp. 415-425.
DOI
|
10 |
Jack, L.B. and Nandi, A.K., "Fault Detection Using Support Vector Machines and Artificial Neural Networks, Augmented by Genetic Algorithms," Mechanical Systems and Signal Processing, Vol.16 (2002), pp. 373-390.
DOI
|
11 |
Kim, K.-j., "Artificial neural networks with evolutionary instance selection for financial forecasting," Expert Systems with Applications, Vol.30, No.3 (2006), pp. 519-526.
DOI
|
12 |
Kim, K.-j. and Ahn, H. "Optimization of Support Vector Machines for Financial Forecasting," Journal of Intelligence and Information Systems, Vol.17, No.4 (2011), pp. 223-236.
|
13 |
Kim, S.W., "Comparison of Predictability of Stock Price Volatility: Focusing on Price Range and VKOSPI," Journal of Korean Data Analysis Society, Vol.13, No.2 (2011), pp. 915-925.
|
14 |
Kim, S. W. and H. C. Ahn, "Development of an Intelligent Trading System using Support Vector Machines and Genetic Algorithms," Journal of Intelligence and Information Systems, Vol.16, No.1(2010), 71-92.
|
15 |
Lee, H., "A Combination Model of Multiple Artificial Intelligence Techniques Based on Genetic Algorithms for the Prediction of Korean Stock Price Index(KOSPI)," Entrue Journal of Information Technology, Vol.7, No.2 (2008), pp. 33-43.
|
16 |
Lee, K., and Byun, H., "A New Face Authentication System for Memory-Constrained Devices," IEEE Transactions on Consumer Electronics, Vol.49, No.4 (2003), pp. 1214-1222.
DOI
|
17 |
Li, L., Tang, H., Wu, Z., Gong, J., Gruidl, M., Zou, J., Tockman, M., Clark, R.A., "Data mining techniques for cancer detection using serum proteomic profiling," Artificial Intelligence in Medicine, Vol.32, No.2 (2004), pp. 71-83.
DOI
|
18 |
Lorena, A.C., and de Carvalho, A.C.P.L,F. "Comparing Techniques for Multiclass Classification Using Binary SVM Predictors," Lecture Notes in Artificial Intelligence, Vol.2972 (2004), pp. 272-281.
|
19 |
Pai, P.-F., and Hong, W.-C. "Forecasting regional electricity load based on recurrent support vector machines with genetic algorithms," Electric Power Systems Research, Vol.74, No.3 (2005), pp. 417-425.
DOI
|
20 |
Lorena, A.C., and de Carvalho, A.C.P.L,F. "Evolutionary tuning of SVM parameter values in multiclass problems," Neurocomputing, Vol.71, Nos.16-18 (2008), pp. 3326-3334.
DOI
|
21 |
Ra, Y.S., H. S. Choi, and S.W. Kim, " VKOSPI Forecasting and Option Trading Application Using SVM," Journal of Intelligence and Information Systems, Vol.22, No.4(2016), 177-192.
DOI
|
22 |
Reeves, C.R., Taylor, S.J., "Selection of training sets for neural networks by a genetic algorithm. In Eiden," A.E., Back, T., Schoenauer M., Schwefel, H.-P., "Parallel problem-solving from nature-PPSN V.," Springer. Berlin (1998)
|
23 |
Shieh, M.-D., and Yang, C.-C. "Multiclass SVM-RFE for product from feature selection," Expert Systems with Applications, Vol.35, Nos.1-2 (2008), pp. 531-541.
DOI
|
24 |
Shin, K.S., and Han. I. "Case-based reasoning supported by genetic algorithms for corporate bond rating," Expert Systems with Applications, Vol.16, No.2 (1999), pp. 85-95.
DOI
|
25 |
Sun, Z., Bebis, G., Miller, R., "Object detection using feature subset selection," Pattern Recognition, Vol.37, No.11 (2004), pp. 2165-2176.
DOI
|
26 |
Thi N., Lee G.-B., Peter W., and Jim P., "GA-SVM Based Framework for Time Series Forecasting," Proceedings of the Fifth International Conference on Natural Computation (2009).
|
27 |
Vapnik, V. The Nature of Statistical Learning Theory. New York, NY: Springer-Verlag, 1995.
|
28 |
Ahn, H., Kim, K.-j., and Han, I., "Intelligent Credit Rating Model for Korean Companies using Multiclass Support Vector Machines," Korean Management Review, Vol. 35, No. 5 (2006), pp. 1479-1496.
|
29 |
Zhao, X.-M., Cheung, Y.-M., Huang, D.-S., "A novel approach to extracting features from motif content and protein composition for protein sequence classification," Neural Networks, Vol.18, No.8 (2005), pp. 1019-1028.
DOI
|
30 |
Wu, C.H., Tzeng, G.H., Goo, Y.J., and Fang, W.C. "A real-valued genetic algorithm to optimize the parameters of support vector machine for prediction bankruptcy," Expert Systems with Applications, Vol. 32, No. 2 (2007), pp. 397-408.
DOI
|
31 |
Ahn, H., and Kim, K.-j. "Corporate Bond Rating Using Various Multiclass Support Vector Machines", Asia Pacific Journal of Information Systems, Vol.19, No.2(2009), pp. 157-178.
|