A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
Neurocomputing
Bankruptcy prediction using neural networks
Decision Support Systems - Special issue on neural networks for decision support
Application of fuzzy ARTMAP and ART-EMAP to automatic target recognition using radar range profiles
Neural Networks - Special issue: automatic target recognition
Hybrid neural network models for bankruptcy predictions
Decision Support Systems
Hybrid Classifiers for Financial Multicriteria Decision Making: TheCase of Bankruptcy Prediction
Computational Economics
An introduction to variable and feature selection
The Journal of Machine Learning Research
Learning polynomial networks for classification of clinical electroencephalograms
Soft Computing - A Fusion of Foundations, Methodologies and Applications
GMDH-based feature ranking and selection for improved classification of medical data
Journal of Biomedical Informatics
Soft computing system for bank performance prediction
Applied Soft Computing
Software development cost estimation using wavelet neural networks
Journal of Systems and Software
Fuzzy ARTMAP Neural Network for Classifying the Financial Health of a Firm
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Ranking-order case-based reasoning for financial distress prediction
Knowledge-Based Systems
Letters: Energy demand prediction using GMDH networks
Neurocomputing
Feature selection in bankruptcy prediction
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
Electric load forecasting using a fuzzy ART&ARTMAP neural network
Applied Soft Computing
Financial distress prediction by a radial basis function network with logit analysis learning
Computers & Mathematics with Applications
Bankruptcy prediction for credit risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A new Fruit Fly Optimization Algorithm: Taking the financial distress model as an example
Knowledge-Based Systems
A hybrid device for the solution of sampling bias problems in the forecasting of firms' bankruptcy
Expert Systems with Applications: An International Journal
Evaluation of banks insolvency using artificial neural networks
AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
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This paper presents three hitherto unused neural network architectures for bankruptcy prediction in banks. These networks are Group Method of Data Handling (GMDH), Counter Propagation Neural Network (CPNN) and fuzzy Adaptive Resonance Theory Map (fuzzy ARTMAP). Efficacy of each of these techniques is tested by using four different datasets pertaining to Spanish banks, Turkish banks, UK banks and US banks. Further t-statistic, f-statistic and GMDH are used for feature selection purpose and the features so selected are fed as input to GMDH, CPNN and fuzzy ARTMAP for classification purpose. In each of these cases, top five features are selected in the case of Spanish dataset and top seven features are selected in the case of Turkish and UK datasets. It is observed that the features selected by t-statistic and f-statistic are identical in all datasets. Further, there is a good overlap in the features selected by t-statistic and GMDH. The performance of these hybrids is compared with that of GMDH, CPNN and fuzzy ARTMAP in their stand-alone mode without feature selection. Ten-fold cross validation is performed throughout the study. Results indicate that the GMDH outperformed all the techniques with or without feature selection. Furthermore, the results are much better than those reported in previous studies on the same datasets in terms of average accuracy, average sensitivity and average specificity.