Hybrid Genetic Programming-Based Search Algorithms for Enterprise bankruptcy Prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{journals/aai/DivsalarJGSM11,
  author =       "Mehdi Divsalar and Mohamad Rezi Javid and 
                 Amir Hossein Gandomi and Jahaniar Bamdad Soofi and 
                 Majid Vesali Mahmood",
  title =        "Hybrid Genetic Programming-Based Search Algorithms for
                 Enterprise bankruptcy Prediction",
  journal =      "Applied Artificial Intelligence",
  year =         "2011",
  volume =       "25",
  number =       "8",
  pages =        "669--692",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1080/08839514.2011.595975",
  size =         "24 pages",
  abstract =     "Bankruptcy is an extremely significant worldwide
                 problem that affects the economic well- being of all
                 countries. The high social costs incurred by various
                 stakeholders associated with bankrupt firms imply the
                 need to search for better theoretical understanding and
                 prediction quality. The main objective of this paper is
                 to apply genetic programming with orthogonal least
                 squares (GP/OLS) and with simulated annealing (GP/SA)
                 algorithms to build models for bankruptcy prediction.
                 Using the hybrid GP/OLS and GP/SA techniques,
                 generalised relationships are obtained to classify
                 samples of 136 bankrupt and nonbankrupt Iranian
                 corporations based on financial ratios. Another
                 important contribution of this paper is to identify the
                 effective predictive financial ratios based on an
                 extensive bankruptcy prediction literature review and a
                 sequential feature selection (SFS) analysis. A
                 comparative study on the classification accuracy of the
                 GP/OLS- and GP/SA-based models is also conducted. The
                 observed agreement between the predictions and the
                 actual values indicates that the proposed models
                 effectively estimate any enterprise with regard to the
                 aspect of bankruptcy. According to the results, the
                 proposed GP/SA model has better performance than the
                 GP/OLS model in bankruptcy prediction.",
  bibdate =      "2011-09-23",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/aai/aai25.html#DivsalarJGSM11",
}

Genetic Programming entries for Mehdi Divsalar Mohamad Reza Javid A H Gandomi Jahaniar Bamdad Soofi Majid Vesali Mahmood

Citations