메뉴 건너뛰기




Volumn 42, Issue 6, 2015, Pages 2857-2869

Bankruptcy visualization and prediction using neural networks: A study of U.S. commercial banks

Author keywords

Bankruptcy prediction; Financial crisis; Multilayer perceptron; Neural networks; Self organizing maps

Indexed keywords

CONFORMAL MAPPING; FORECASTING; MULTILAYERS; NEURAL NETWORKS; RISK ASSESSMENT; SELF ORGANIZING MAPS;

EID: 84949114958     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2014.11.025     Document Type: Article
Times cited : (159)

References (79)
  • 2
    • 84980104458 scopus 로고
    • Financial ratios, discriminant analysis and prediction of corporate bankruptcy
    • Altman, E. (1968). Financial ratios, discriminant analysis and prediction of corporate bankruptcy. Journal of Finance, 23, 589-609.
    • (1968) Journal of Finance , vol.23 , pp. 589-609
    • Altman, E.1
  • 3
    • 43949151078 scopus 로고
    • Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks
    • Altman, E., Marco, G., & Varetto, F. (1994). Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks. Journal of Banking and Finance, 18, 505-529.
    • (1994) Journal of Banking and Finance , vol.18 , pp. 505-529
    • Altman, E.1    Marco, G.2    Varetto, F.3
  • 5
    • 0035391093 scopus 로고    scopus 로고
    • Bankruptcy prediction for credit risk using neural networks: A survey and new results
    • Atiya, A. F. (2001). Bankruptcy prediction for credit risk using neural networks: A survey and new results. IEEE Transactions on Neural Networks, 12, 929-935.
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 929-935
    • Atiya, A.F.1
  • 6
    • 0002554419 scopus 로고
    • Financial ratios as predictors of failure
    • Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accountant Research, 4, 71-111.
    • (1966) Journal of Accountant Research , vol.4 , pp. 71-111
    • Beaver, W.H.1
  • 8
    • 84891714796 scopus 로고    scopus 로고
    • Automated trading with performance weighted random forests and seasonality
    • Booth, A., Gerding, E., & McGroarty, F. (2014). Automated trading with performance weighted random forests and seasonality. Expert Systems with Applications, 41, 3651-3661.
    • (2014) Expert Systems with Applications , vol.41 , pp. 3651-3661
    • Booth, A.1    Gerding, E.2    McGroarty, F.3
  • 9
    • 0029492199 scopus 로고
    • Effectiveness of neural networks types for prediction of business failure
    • Boritz, J. E., & Kennedy, D. B. (1995). Effectiveness of neural networks types for prediction of business failure. Expert Systems with Applications, 9, 503-512.
    • (1995) Expert Systems with Applications , vol.9 , pp. 503-512
    • Boritz, J.E.1    Kennedy, D.B.2
  • 10
    • 56349142889 scopus 로고    scopus 로고
    • Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey
    • Boyacioglu, M. A., Kara, Y., & Baykan, Ö. K. (2009). Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey. Expert Systems with Applications, 36, 3355-3366.
    • (2009) Expert Systems with Applications , vol.36 , pp. 3355-3366
    • Boyacioglu, M.A.1    Kara, Y.2    Baykan, Ö.K.3
  • 11
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman, L. (2001). Random forests. Machine Learning, 45, 5-32.
    • (2001) Machine Learning , vol.45 , pp. 5-32
    • Breiman, L.1
  • 12
    • 84906569541 scopus 로고    scopus 로고
    • Indoor localization in a hospital environment using random forest classifiers
    • Calderoni, L., Ferrara, M., Franco, A., & Maio, D. (2015). Indoor localization in a hospital environment using random forest classifiers. Expert Systems with Applications, 42, 125-134.
    • (2015) Expert Systems with Applications , vol.42 , pp. 125-134
    • Calderoni, L.1    Ferrara, M.2    Franco, A.3    Maio, D.4
  • 14
    • 84904336047 scopus 로고    scopus 로고
    • Credit rating with a monotonicity-constrained support vector machine model
    • Chen, C.-C., & Li, S.-T. (2014). Credit rating with a monotonicity-constrained support vector machine model. Expert Systems with Applications, 41, 7235-7247.
    • (2014) Expert Systems with Applications , vol.41 , pp. 7235-7247
    • Chen, C.-C.1    Li, S.-T.2
  • 15
    • 82255175559 scopus 로고    scopus 로고
    • Bankruptcy prediction in firms with statistical and intelligent techniques and a comparison of evolutionary computation approaches
    • Chen, M.-Y. (2011a). Bankruptcy prediction in firms with statistical and intelligent techniques and a comparison of evolutionary computation approaches. Computers & Mathematics with Applications, 62, 4514-4524.
    • (2011) Computers & Mathematics with Applications , vol.62 , pp. 4514-4524
    • Chen, M.-Y.1
  • 16
    • 79955621501 scopus 로고    scopus 로고
    • Predicting corporate financial distress based on integration of decision tree classification and logistic regression
    • Chen, M.-Y. (2011b). Predicting corporate financial distress based on integration of decision tree classification and logistic regression. Expert Systems with Applications, 38, 11261-11272.
    • (2011) Expert Systems with Applications , vol.38 , pp. 11261-11272
    • Chen, M.-Y.1
  • 17
    • 84866105753 scopus 로고    scopus 로고
    • Clustering and visualization of bankruptcy trajectory using self-organizing map
    • Chen, N., Ribeiro, B., Vieira, A., & Chen, A. (2013). Clustering and visualization of bankruptcy trajectory using self-organizing map. Expert Systems with Applications, 40, 385-393.
    • (2013) Expert Systems with Applications , vol.40 , pp. 385-393
    • Chen, N.1    Ribeiro, B.2    Vieira, A.3    Chen, A.4
  • 20
    • 43049103128 scopus 로고    scopus 로고
    • Comparing early warning systems for banking crises
    • Davis, E. P., & Karim, D. (2008). Comparing early warning systems for banking crises. Journal of Financial Stability, 4, 89-120.
    • (2008) Journal of Financial Stability , vol.4 , pp. 89-120
    • Davis, E.P.1    Karim, D.2
  • 21
    • 77952537146 scopus 로고    scopus 로고
    • Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy
    • du Jardin, P. (2010). Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy. Neurocomputing, 73 , 2047-2060.
    • (2010) Neurocomputing , vol.73 , pp. 2047-2060
    • Du Jardin, P.1
  • 22
    • 84882706559 scopus 로고    scopus 로고
    • Prediction of bankruptcy using support vector machines: An application to bank bankruptcy
    • Erdogan, B. E. (2012). Prediction of bankruptcy using support vector machines: An application to bank bankruptcy. Journal of Statistical Computation and Simulation, 83, 1543-1555.
    • (2012) Journal of Statistical Computation and Simulation , vol.83 , pp. 1543-1555
    • Erdogan, B.E.1
  • 23
    • 84881415129 scopus 로고    scopus 로고
    • Bankruptcy prediction for Russian companies: Application of combined classifiers
    • Fedorova, E., Gilenko, E., & Dovzhenko, S. (2013). Bankruptcy prediction for Russian companies: Application of combined classifiers. Expert Systems with Applications, 40, 7285-7293.
    • (2013) Expert Systems with Applications , vol.40 , pp. 7285-7293
    • Fedorova, E.1    Gilenko, E.2    Dovzhenko, S.3
  • 25
    • 0000602068 scopus 로고
    • A comparison of neural network and expert systems algorithms with common multivariate procedures for analysis of social science data
    • Garson, G. D. (1991). A comparison of neural network and expert systems algorithms with common multivariate procedures for analysis of social science data. Social Science Computer Review, 9, 399-434.
    • (1991) Social Science Computer Review , vol.9 , pp. 399-434
    • Garson, G.D.1
  • 27
    • 84876046068 scopus 로고    scopus 로고
    • Quantitative credit risk assessment using support vector machines: Broad versus narrow default definitions
    • Harris, T. (2013). Quantitative credit risk assessment using support vector machines: Broad versus narrow default definitions. Expert Systems with Applications, 40, 4404-4413.
    • (2013) Expert Systems with Applications , vol.40 , pp. 4404-4413
    • Harris, T.1
  • 28
    • 84907481786 scopus 로고    scopus 로고
    • Credit scoring using the clustered support vector machine
    • Harris, T. (2015). Credit scoring using the clustered support vector machine. Expert Systems with Applications, 42, 741-750.
    • (2015) Expert Systems with Applications , vol.42 , pp. 741-750
    • Harris, T.1
  • 30
    • 84879466018 scopus 로고    scopus 로고
    • Company failure prediction in the construction industry
    • Horta, I. M., & Camanho, A. S. (2013). Company failure prediction in the construction industry. Expert Systems with Applications, 40, 6253-6257.
    • (2013) Expert Systems with Applications , vol.40 , pp. 6253-6257
    • Horta, I.M.1    Camanho, A.S.2
  • 31
    • 84906569534 scopus 로고    scopus 로고
    • A proposed iteration optimization approach integrating backpropagation neural network with genetic algorithm
    • Huang, H.-X., Li, J.-C., & Xiao, C.-L. (2015). A proposed iteration optimization approach integrating backpropagation neural network with genetic algorithm. Expert Systems with Applications, 42, 146-155.
    • (2015) Expert Systems with Applications , vol.42 , pp. 146-155
    • Huang, H.-X.1    Li, J.-C.2    Xiao, C.-L.3
  • 32
    • 0033623037 scopus 로고    scopus 로고
    • Application of neural networks and sensitivity analysis to improved prediction of trauma survival
    • Hunter, A., Kennedy, L., Henry, J., & Ferguson, I. (2000). Application of neural networks and sensitivity analysis to improved prediction of trauma survival. Computer Methods and Programs in Biomedicine, 62, 11-19.
    • (2000) Computer Methods and Programs in Biomedicine , vol.62 , pp. 11-19
    • Hunter, A.1    Kennedy, L.2    Henry, J.3    Ferguson, I.4
  • 35
    • 0028571742 scopus 로고
    • Winner-take-all networks for physiological models of competitive learning
    • Kaski, S., & Kohonen, T. (1994). Winner-take-all networks for physiological models of competitive learning. Neural Networks, 7, 973-984.
    • (1994) Neural Networks , vol.7 , pp. 973-984
    • Kaski, S.1    Kohonen, T.2
  • 36
    • 78649516309 scopus 로고    scopus 로고
    • Neural networks for credit risk evaluation: Investigation of different neural models and learning schemes
    • Khashman, A. (2010). Neural networks for credit risk evaluation: Investigation of different neural models and learning schemes. Expert Systems with Applications, 37, 6233-6239.
    • (2010) Expert Systems with Applications , vol.37 , pp. 6233-6239
    • Khashman, A.1
  • 37
    • 0345404391 scopus 로고    scopus 로고
    • Predicting bankruptcies with the self-organizing map
    • Kiviluoto, K. (1998). Predicting bankruptcies with the self-organizing map. Neurocomputing, 21, 191-201.
    • (1998) Neurocomputing , vol.21 , pp. 191-201
    • Kiviluoto, K.1
  • 38
    • 0027806867 scopus 로고
    • Physiological interpretation of the self-organizating map algorithm
    • Kohonen, T. (1993). Physiological interpretation of the self-organizating map algorithm. Neural Networks, 6, 895-905.
    • (1993) Neural Networks , vol.6 , pp. 895-905
    • Kohonen, T.1
  • 39
    • 84904191292 scopus 로고    scopus 로고
    • Detecting corn tassels using computer vision and support vector machines
    • Kurtulmuş, F., & Kavdir, I. (2014). Detecting corn tassels using computer vision and support vector machines. Expert Systems with Applications, 41 , 7390-7397.
    • (2014) Expert Systems with Applications , vol.41 , pp. 7390-7397
    • Kurtulmuş, F.1    Kavdir, I.2
  • 40
    • 16244365542 scopus 로고    scopus 로고
    • A comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms
    • Lee, K., Booth, D., & Alam, P. (2005). A comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms. Expert Systems with Applications, 29, 1-16.
    • (2005) Expert Systems with Applications , vol.29 , pp. 1-16
    • Lee, K.1    Booth, D.2    Alam, P.3
  • 41
    • 84874648833 scopus 로고    scopus 로고
    • A multi-industry bankruptcy prediction model using back-propagation neural network and multivariate discriminant analysis
    • Lee, S., & Choi, W. S. (2013). A multi-industry bankruptcy prediction model using back-propagation neural network and multivariate discriminant analysis. Expert Systems with Applications, 40, 2941-2946.
    • (2013) Expert Systems with Applications , vol.40 , pp. 2941-2946
    • Lee, S.1    Choi, W.S.2
  • 43
    • 80052037005 scopus 로고    scopus 로고
    • Financial ratio selection for business crisis prediction
    • Lin, F., Liang, D., & Chen, E. (2011). Financial ratio selection for business crisis prediction. Expert Systems with Applications, 38 , 15094-15102.
    • (2011) Expert Systems with Applications , vol.38 , pp. 15094-15102
    • Lin, F.1    Liang, D.2    Chen, E.3
  • 44
    • 67349100659 scopus 로고    scopus 로고
    • Applying enhanced data mining approaches in predicting bank performance. A case of Taiwanese commercial banks
    • Lin, S. W., Shiue, Y. R., Chen, S. C., & Cheng, H. M. (2009). Applying enhanced data mining approaches in predicting bank performance. A case of Taiwanese commercial banks. Expert Systems with Applications, 36, 11543-11551.
    • (2009) Expert Systems with Applications , vol.36 , pp. 11543-11551
    • Lin, S.W.1    Shiue, Y.R.2    Chen, S.C.3    Cheng, H.M.4
  • 45
    • 77955035457 scopus 로고    scopus 로고
    • Forecasting company failure: Neural approach versus discriminant analysis: An application to Spanish insurance companies
    • G. Sierra Molina & E. Bonsón Ponte (Eds.), Huelva
    • Martínez, I. (1996). Forecasting company failure: Neural approach versus discriminant analysis: An application to Spanish insurance companies. In: G. Sierra Molina & E. Bonsón Ponte (Eds.), Intelligent systems in accounting and finance (pp. 169-185). Huelva.
    • (1996) Intelligent Systems in Accounting and Finance , pp. 169-185
    • Martínez, I.1
  • 47
    • 17844363481 scopus 로고    scopus 로고
    • Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
    • Min, J. H., & Lee, Y.-C. (2005). Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters. Expert Systems with Applications, 28, 603-614.
    • (2005) Expert Systems with Applications , vol.28 , pp. 603-614
    • Min, J.H.1    Lee, Y.-C.2
  • 48
    • 79953675053 scopus 로고    scopus 로고
    • Financial health prediction models using artificial neural networks, genetic algorithm and multivariate discriminant analysis: Iranian evidence
    • Mokhatab Rafiei, F., Manzari, S. M., & Bostanian, S. (2011). Financial health prediction models using artificial neural networks, genetic algorithm and multivariate discriminant analysis: Iranian evidence. Expert Systems with Applications, 38, 10210-10217.
    • (2011) Expert Systems with Applications , vol.38 , pp. 10210-10217
    • Mokhatab Rafiei, F.1    Manzari, S.M.2    Bostanian, S.3
  • 49
    • 84908042352 scopus 로고    scopus 로고
    • Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation
    • Moro, S., Cortez, P., & Rita, P. (2015). Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, 42, 1314-1324.
    • (2015) Expert Systems with Applications , vol.42 , pp. 1314-1324
    • Moro, S.1    Cortez, P.2    Rita, P.3
  • 50
    • 53849126165 scopus 로고    scopus 로고
    • Neural networks and statistical techniques: A review of applications
    • Mukta, P., & Kumar, U. A. (2009). Neural networks and statistical techniques: A review of applications. Expert Systems with Applications, 36, 2-17.
    • (2009) Expert Systems with Applications , vol.36 , pp. 2-17
    • Mukta, P.1    Kumar, U.A.2
  • 53
    • 0000666375 scopus 로고
    • Financial ratios and probabilistic prediction of bankruptcy
    • Ohlson, J. (1980). Financial ratios and probabilistic prediction of bankruptcy. Journal of Accounting Research, 18, 109-131.
    • (1980) Journal of Accounting Research , vol.18 , pp. 109-131
    • Ohlson, J.1
  • 54
    • 0004401956 scopus 로고    scopus 로고
    • Hybrid classifier for financial multicriteria decision making: The case of bankruptcy prediction
    • Olmeda, I., & Fernández, E. (1997). Hybrid classifier for financial multicriteria decision making: The case of bankruptcy prediction. Computational Economics, 10, 317-335.
    • (1997) Computational Economics , vol.10 , pp. 317-335
    • Olmeda, I.1    Fernández, E.2
  • 55
    • 84888315345 scopus 로고    scopus 로고
    • Genetic algorithm-based heuristic for feature selection in credit risk assessment
    • Oreski, S., & Oreski, G. (2014). Genetic algorithm-based heuristic for feature selection in credit risk assessment. Expert Systems with Applications, 41, 2052-2064.
    • (2014) Expert Systems with Applications , vol.41 , pp. 2052-2064
    • Oreski, S.1    Oreski, G.2
  • 56
    • 0032749972 scopus 로고    scopus 로고
    • Financial credit-risk evaluation with neural and neurofuzzy systems
    • Piramuthu, S. (1999). Financial credit-risk evaluation with neural and neurofuzzy systems. European Journal of Operational Research, 112, 310-321.
    • (1999) European Journal of Operational Research , vol.112 , pp. 310-321
    • Piramuthu, S.1
  • 58
    • 84857656368 scopus 로고    scopus 로고
    • A hybrid device for the solution of sampling bias problems in the forecasting of firms' bankruptcy
    • Sánchez-Lasheras, F., de Andrés, J., Lorca, P., & de Cos Juez, F. J. (2012). A hybrid device for the solution of sampling bias problems in the forecasting of firms' bankruptcy. Expert Systems with Applications, 39, 7512-7523.
    • (2012) Expert Systems with Applications , vol.39 , pp. 7512-7523
    • Sánchez-Lasheras, F.1    De Andrés, J.2    Lorca, P.3    De Cos Juez, F.J.4
  • 59
    • 0030190036 scopus 로고    scopus 로고
    • Self-organizing neural networks for financial diagnosis
    • Serrano-Cinca, C. (1996). Self-organizing neural networks for financial diagnosis. Decision Support Systems, 17, 217-228.
    • (1996) Decision Support Systems , vol.17 , pp. 217-228
    • Serrano-Cinca, C.1
  • 60
    • 84875427238 scopus 로고    scopus 로고
    • Partial least square discriminant analysis for bankruptcy prediction
    • Serrano-Cinca, C., & Gutiérrez-Nieto, B. (2013). Partial least square discriminant analysis for bankruptcy prediction. Decision Support Systems, 54, 1245-1255.
    • (2013) Decision Support Systems , vol.54 , pp. 1245-1255
    • Serrano-Cinca, C.1    Gutiérrez-Nieto, B.2
  • 61
    • 0000669406 scopus 로고    scopus 로고
    • Neural network experiments in business-failure forecasting: Predictive performance measurement issues
    • Sharda, R., & Wilson, R. L. (1996). Neural network experiments in business-failure forecasting: predictive performance measurement issues. International Journal of Computational Intelligence and Organization, 1, 107-117.
    • (1996) International Journal of Computational Intelligence and Organization , vol.1 , pp. 107-117
    • Sharda, R.1    Wilson, R.L.2
  • 62
    • 84894901583 scopus 로고    scopus 로고
    • Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches
    • Sun, J., Li, H., Huang, Q.-H., & He, K.-Y. (2014). Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches. Knowledge-Based Systems, 57, 41-56.
    • (2014) Knowledge-Based Systems , vol.57 , pp. 41-56
    • Sun, J.1    Li, H.2    Huang, Q.-H.3    He, K.-Y.4
  • 63
    • 33846279365 scopus 로고
    • Predicting bank failures: A neural network approach
    • Tam, K. Y., & Kiang, M. (1992). Predicting bank failures: A neural network approach. Decision Sciences, 3, 926-947.
    • (1992) Decision Sciences , vol.3 , pp. 926-947
    • Tam, K.Y.1    Kiang, M.2
  • 64
    • 84908455123 scopus 로고    scopus 로고
    • A comparative study of classifier ensembles for bankruptcy prediction
    • Tsai, C.-F., Hsu, Y.-F., & Yen, D. C. (2014). A comparative study of classifier ensembles for bankruptcy prediction. Applied Soft Computing, 24, 977-984.
    • (2014) Applied Soft Computing , vol.24 , pp. 977-984
    • Tsai, C.-F.1    Hsu, Y.-F.2    Yen, D.C.3
  • 66
    • 2042515742 scopus 로고    scopus 로고
    • Neural networks in business: A survey of applications (1992-1998)
    • Vellido, A., Lisboa, P., & Vaughan, J. (1999). Neural networks in business: A survey of applications (1992-1998). Expert Systems with Applications, 17, 51-70.
    • (1999) Expert Systems with Applications , vol.17 , pp. 51-70
    • Vellido, A.1    Lisboa, P.2    Vaughan, J.3
  • 67
    • 84890117005 scopus 로고    scopus 로고
    • An improved boosting based on feature selection for corporate bankruptcy prediction
    • Wang, G., Ma, J., & Yang, S. (2014). An improved boosting based on feature selection for corporate bankruptcy prediction. Expert Systems with Applications, 41, 2353-2361.
    • (2014) Expert Systems with Applications , vol.41 , pp. 2353-2361
    • Wang, G.1    Ma, J.2    Yang, S.3
  • 68
    • 84907494099 scopus 로고    scopus 로고
    • Back propagation neural network with adaptive differential evolution algorithm for time series forecasting
    • Wang, L., Zeng, Y., & Chen, T. (2015). Back propagation neural network with adaptive differential evolution algorithm for time series forecasting. Expert Systems with Applications, 42, 855-863.
    • (2015) Expert Systems with Applications , vol.42 , pp. 855-863
    • Wang, L.1    Zeng, Y.2    Chen, T.3
  • 70
    • 27744530025 scopus 로고    scopus 로고
    • A neural network approach for analyzing small business lending decisions
    • Wu, C., & Wang, X. M. (2000). A neural network approach for analyzing small business lending decisions. Review of Quantitative Finance and Accounting, 15, 259-276.
    • (2000) Review of Quantitative Finance and Accounting , vol.15 , pp. 259-276
    • Wu, C.1    Wang, X.M.2
  • 72
    • 58349116623 scopus 로고    scopus 로고
    • Customer churn prediction using improved balanced random forests
    • Xie, Y., Li, X., Ngai, E., & Ying, W. (2009). Customer churn prediction using improved balanced random forests. Expert Systems with Applications, 36, 5445-5449.
    • (2009) Expert Systems with Applications , vol.36 , pp. 5445-5449
    • Xie, Y.1    Li, X.2    Ngai, E.3    Ying, W.4
  • 73
    • 84899989388 scopus 로고    scopus 로고
    • Financial ratio selection for business failure prediction using soft set theory
    • Xu, W., Xiao, Z., Dang, X., Yang, D., & Yang, X. (2014). Financial ratio selection for business failure prediction using soft set theory. Knowledge-Based Systems, 63, 59-67.
    • (2014) Knowledge-Based Systems , vol.63 , pp. 59-67
    • Xu, W.1    Xiao, Z.2    Dang, X.3    Yang, D.4    Yang, X.5
  • 74
    • 9244223578 scopus 로고    scopus 로고
    • Comparison of country risk models: Hybrid neural networks, logit models, discriminant analysis and cluster techniques
    • Yin, J. (2005). Comparison of country risk models: hybrid neural networks, logit models, discriminant analysis and cluster techniques. Expert Systems with Applications, 28, 137-148.
    • (2005) Expert Systems with Applications , vol.28 , pp. 137-148
    • Yin, J.1
  • 75
    • 84893091209 scopus 로고    scopus 로고
    • Bankruptcy prediction using extreme learning machine and financial expertise
    • Yu, Q., Miche, Y., Séverin, E., & Lendasse, A. (2014). Bankruptcy prediction using extreme learning machine and financial expertise. Neurocomputing, 128, 296-302.
    • (2014) Neurocomputing , vol.128 , pp. 296-302
    • Yu, Q.1    Miche, Y.2    Séverin, E.3    Lendasse, A.4
  • 76
    • 0032640524 scopus 로고    scopus 로고
    • Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis
    • Zhang, H., Hu, M. Y., Patuwo, B. E., & Indro, D. C. (1999). Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis. European Journal of Operational Research, 116, 16-32.
    • (1999) European Journal of Operational Research , vol.116 , pp. 16-32
    • Zhang, H.1    Hu, M.Y.2    Patuwo, B.E.3    Indro, D.C.4
  • 77
    • 84873725663 scopus 로고    scopus 로고
    • Performance of corporate bankruptcy prediction models on imbalanced dataset: The effect of sampling methods
    • Zhou, L. (2013). Performance of corporate bankruptcy prediction models on imbalanced dataset: The effect of sampling methods. Knowledge-Based Systems, 41, 16-25.
    • (2013) Knowledge-Based Systems , vol.41 , pp. 16-25
    • Zhou, L.1
  • 78
    • 84884893168 scopus 로고    scopus 로고
    • Bankruptcy prediction using SVM models with a new approach to combine features selection and parameter optimisation
    • Zhou, L., Lai, K. K., & Yen, J. (2012). Bankruptcy prediction using SVM models with a new approach to combine features selection and parameter optimisation. International Journal of Systems Science, 45, 241-253.
    • (2012) International Journal of Systems Science , vol.45 , pp. 241-253
    • Zhou, L.1    Lai, K.K.2    Yen, J.3
  • 79
    • 0028570720 scopus 로고
    • Sensitivity analysis for minimization of input data dimension for feedforward neural network
    • Zurada, J. M., Malinowski, A., & Cloete, I., 1994. Sensitivity analysis for minimization of input data dimension for feedforward neural network. In: Proceedings of ISCAS'1994 (vol. 10, pp. 447-450).
    • (1994) Proceedings of ISCAS'1994 , vol.10 , pp. 447-450
    • Zurada, J.M.1    Malinowski, A.2    Cloete, I.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.