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The integrated methodology of rough set theory and artificial neural network for business failure prediction
10 references·16 citing·32 second hop
The integrated methodology of rough set theory and artificial neural network for business failure prediction (2000)The integrated methodology of rough set t…Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) (1994)Corporate distress diagnosis:…Forecasting with neural networks (1993)Forecasting with neural netwo…Neural Networks: A New Tool for Predicting Thrift Failures* (1992)Neural Networks: A New Tool f…Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Managerial Applications of Ne…Intelligent Decision Support (1992)Intelligent Decision SupportA neural network model for bankruptcy prediction (1990)A neural network model for ba…ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)ZETATM analysis A new model t…Bankruptcy Costs: Some Evidence (1977)Bankruptcy Costs: Some Eviden…BANKRUPTCY COSTS: SOME EVIDENCE (1977)BANKRUPTCY COSTS: SOME EVIDEN…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Artificial intelligence for decision support systems in the field of operations research: review and future scope of research (2021)Artificial intelligence for d…Systematic review of bankruptcy prediction models: Towards a framework for tool selection (2017)Systematic review of bankrupt…Hybrid genetic algorithm and fuzzy clustering for bankruptcy prediction (2017)Hybrid genetic algorithm and …Bankruptcy prediction for SMEs using relational data (2017)Bankruptcy prediction for SME…Credit risk evaluation using neural networks: Emotional versus conventional models (2011)Credit risk evaluation using …Neural networks for credit risk evaluation: Investigation of different neural models and learning schemes (2010)Neural networks for credit ri…Bankruptcy forecasting: A hybrid approach using Fuzzy c-means clustering and Multivariate Adaptive Regression Splines (MARS) (2010)Bankruptcy forecasting: A hyb…Hybrid and ensemble-based soft computing techniques in bankruptcy prediction: a survey (2009)Hybrid and ensemble-based sof…A hybrid approach of DEA, rough set and support vector machines for business failure prediction (2009)A hybrid approach of DEA, rou…Ranking-order case-based reasoning for financial distress prediction (2008)Ranking-order case-based reas…Soft computing system for bank performance prediction (2007)Soft computing system for ban…Nonlinear neural network forecasting model for stock index option price: Hybrid GJR–GARCH approach (2007)Nonlinear neural network fore…Forecasting financial condition of Chinese listed companies based on support vector machine (2007)Forecasting financial conditi…Two-stage genetic programming (2SGP) for the credit scoring model (2005)Two-stage genetic programming…The evaluation of consumer loans using support vector machines (2005)The evaluation of consumer lo…Applying rough sets to market timing decisions (2003)Applying rough sets to market…The Predictive Sample Reuse Method with Applications (1975)International Business Cycles and the ERM: Is There a European Business Cycle? 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this work references cited by second hop

References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1977ZETATM analysis A new model to identify bankruptcy risk of corporations1,812 cited
  • 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions1,121 cited
  • 1977BANKRUPTCY COSTS: SOME EVIDENCE1,096 cited
  • 1994Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)1,059 cited
  • 1977Bankruptcy Costs: Some Evidence879 cited
  • 1990A neural network model for bankruptcy prediction853 cited
  • 1992Intelligent Decision Support836 cited
  • 1992Neural Networks: A New Tool for Predicting Thrift Failures*533 cited
  • 1993Forecasting with neural networks432 cited

Cited by

  • 2017Systematic review of bankruptcy prediction models: Towards a framework for tool selection330 cited
  • 2021Artificial intelligence for decision support systems in the field of operations research: review and future scope of research323 cited
  • 2007Forecasting financial condition of Chinese listed companies based on support vector machine246 cited
  • 2010Neural networks for credit risk evaluation: Investigation of different neural models and learning schemes236 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2007Soft computing system for bank performance prediction173 cited
  • 2010Bankruptcy forecasting: A hybrid approach using Fuzzy c-means clustering and Multivariate Adaptive Regression Splines (MARS)169 cited
  • 2009Hybrid and ensemble-based soft computing techniques in bankruptcy prediction: a survey168 cited
  • 2009A hybrid approach of DEA, rough set and support vector machines for business failure prediction167 cited
  • 2005Two-stage genetic programming (2SGP) for the credit scoring model163 cited
  • 2008Ranking-order case-based reasoning for financial distress prediction141 cited
  • 2007Nonlinear neural network forecasting model for stock index option price: Hybrid GJR–GARCH approach141 cited
  • 2003Applying rough sets to market timing decisions141 cited
  • 2005The evaluation of consumer loans using support vector machines135 cited
  • 2017Hybrid genetic algorithm and fuzzy clustering for bankruptcy prediction126 cited
  • 2017Bankruptcy prediction for SMEs using relational data122 cited
  • 2011Credit risk evaluation using neural networks: Emotional versus conventional models102 cited