Grammatical Evolution And Corporate Failure Prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{brabazon:2002:gecco,

• author = "Anthony Brabazon and Michael O'Neill and Robin Matthews and Conor Ryan",
• title = "Grammatical Evolution And Corporate Failure Prediction",
• booktitle = "GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference",
• editor = "W. B. Langdon and E. Cant{\'u}-Paz and K. Mathias and R. Roy and D. Davis and R. Poli and K. Balakrishnan and V. Honavar and G. Rudolph and J. Wegener and L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and E. Burke and N. Jonoska",
• year = "2002",
• pages = "1011--1018",
• address = "New York",
• publisher_address = "San Francisco, CA 94104, USA",
• month = "9-13 " # jul,
• publisher = "Morgan Kaufmann Publishers",
• keywords = "genetic algorithms, genetic programming, Grammatical Evolution, real world applications, corporate failure prediction, genotype to phenotype mapping, grammars",
• ISBN = "1-55860-878-8",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco2002/RWA145.ps",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco2002/RWA145.pdf",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gecco2002/gecco-2002-20.pdf",
• size = "8 pages",
• abstract = "This study examines the potential of Grammatical Evolution to uncover a series of useful rules which can assist in predicting corporate failure using information drawn from financial statements. A sample of 178 publically quoted, failed and non-failed Us firms, drawn from the period 1991 to 2000 are used to train and test the model. The preliminary findings indicate that the methodology has much potential.",
• notes = "GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002)",

}

Genetic Programming entries for Anthony Brabazon Michael O'Neill Robin Matthews Conor Ryan

Citations