Bankruptcy prediction using neural networks
Decision Support Systems - Special issue on neural networks for decision support
Self organizing neural networks for financial diagnosis
Decision Support Systems
Hybrid neural network models for bankruptcy predictions
Decision Support Systems
Adaptation-guided retrieval: questioning the similarity assumption in reasoning
Artificial Intelligence
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
An introduction to variable and feature selection
The Journal of Machine Learning Research
Foundations of Soft Case-Based Reasoning
Foundations of Soft Case-Based Reasoning
Self-organizing learning array and its application to economic and financial problems
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification
Information Sciences: an International Journal
Fuzzy functions with support vector machines
Information Sciences: an International Journal
Mining competent case bases for case-based reasoning
Artificial Intelligence
Short communication: Data mining method for listed companies' financial distress prediction
Knowledge-Based Systems
A nature inspired Ying-Yang approach for intelligent decision support in bank solvency analysis
Expert Systems with Applications: An International Journal
Using neural network ensembles for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Forecasting financial condition of Chinese listed companies based on support vector machine
Expert Systems with Applications: An International Journal
A rough margin based support vector machine
Information Sciences: an International Journal
A hybrid financial analysis model for business failure prediction
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An association-based case reduction technique for case-based reasoning
Information Sciences: an International Journal
Information Sciences: an International Journal
Support vector regression from simulation data and few experimental samples
Information Sciences: an International Journal
Financial distress early warning based on group decision making
Computers and Operations Research
Expert Systems with Applications: An International Journal
Developing a business failure prediction model via RST, GRA and CBR
Expert Systems with Applications: An International Journal
Majority voting combination of multiple case-based reasoning for financial distress prediction
Expert Systems with Applications: An International Journal
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
Financial distress prediction based on similarity weighted voting CBR
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
A similarity measure for fuzzy rulebases based on linguistic gradients
Information Sciences: an International Journal
An application of support vector machine to companies' financial distress prediction
MDAI'06 Proceedings of the Third international conference on Modeling Decisions for Artificial Intelligence
Loss and gain functions for CBR retrieval
Information Sciences: an International Journal
Predicting business failure using multiple case-based reasoning combined with support vector machine
Expert Systems with Applications: An International Journal
Financial Forecasting of Invoicing and Cash Inflow Processes for Fair Exhibitions
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Business failure prediction using hybrid2 case-based reasoning (H2CBR)
Computers and Operations Research
Multi-agent neural business control system
Information Sciences: an International Journal
Failure prediction of dotcom companies using neural network-genetic programming hybrids
Information Sciences: an International Journal
New model for system behavior prediction based on belief rule based systems
Information Sciences: an International Journal
A case study on financial ratios via cross-graph quasi-bicliques
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A novel CBR system for numeric prediction
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Condition-based maintenance of dynamic systems using online failure prognosis and belief rule base
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A multi-agent system for web-based risk management in small and medium business
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An application of multi-criteria decision aids models for Case-Based Reasoning
Information Sciences: an International Journal
Information Sciences: an International Journal
The Journal of Supercomputing
Engineering Applications of Artificial Intelligence
An improved boosting based on feature selection for corporate bankruptcy prediction
Expert Systems with Applications: An International Journal
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Case-based reasoning (CBR) is an easily understandable concept. Business failure prediction (BFP) is a valuable tool that can assist businesses take appropriate action when faced with the knowledge of the possibility of business failure. This study aims to improve the performance of a CBR system for BFP in terms of accuracy and reliability by constructing a new similarity measure, an area seldom researched in the domain of BFP. In order to fulfill this objective, we present a hybrid Gaussian CBR (GCBR) system and use it in BFP with empirical data in China. The heart of GCBR is similarity measure using Gaussian indicators. Feature distances between a pair of cases on each feature are transferred to Gaussian indicators by Gaussian transformations. A combiner is used to generate case similarity on the basis of the Gaussian indicators. Consensus of nearest neighbors is used to generate forecasting on the basis of case similarity. The new hybrid CBR system was empirically tested with data collected from the Shanghai Stock Exchange and Shenzhen Stock Exchange in China. We statistically validated our results by comparing them with multiple discriminant analysis, logistic regression, and two classical CBR systems. The results indicated that GCBR produces superior performance in short-term BFP of Chinese listed companies in terms of both predictive accuracy and coefficient of variation.