Finding Relevant Variables in a Financial Distress Prediction Problem Using Genetic Programming and Self-organizing Maps
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Publication:3627045
DOI10.1007/978-3-540-95974-8_3zbMath1160.91301OpenAlexW78152419MaRDI QIDQ3627045
Eva Alfaro-Cid, Ken C. Sharman, Anna I. Esparcia-Alcázar, Antonio M. Mora
Publication date: 14 May 2009
Published in: Natural Computing in Computational Finance (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-540-95974-8_3
Economic time series analysis (91B84) Learning and adaptive systems in artificial intelligence (68T05) Computational methods for problems pertaining to game theory, economics, and finance (91-08)
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- Genetic programming for the prediction of insolvency in non-life insurance companies
- Predicting bankruptcies with the self-organizing map
- Biologically inspired algorithms for financial modelling.
- Bankruptcy theory development and classification via genetic programming
- Strong Typing, Variable Reduction and Bloat Control for Solving the Bankruptcy Prediction Problem Using Genetic Programming
- Self-organizing maps.
- Comparative analysis of artificial neural network models: Application in bankruptcy prediction
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