@inproceedings{white:2005:CEC,
title = {A Statistical Comparison of Grammatical Evolution
Strategies in the Domain of Human Genetics},
address = {Edinburgh, UK},
author = {Bill C. White and Joshua C. Gilbert and David M. Reif and Jason H. Moore},
booktitle = {Proceedings of the 2005 IEEE Congress on Evolutionary
Computation},
editor = {David Corne and Zbigniew Michalewicz and Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and Garrison Greenwood and Tan Kay Chen and Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and Jennifier Willies and Juan J. Merelo Guervos and Eugene Eberbach and Bob McKay and Alastair Channon and Ashutosh Tiwari and L. Gwenn Volkert and Dan Ashlock and Marc Schoenauer},
month = {2-5 September},
pages = {491--497},
publisher = {IEEE Press},
volume = {1},
year = {2005},
abstract = {Detecting and characterising genetic predictors of
human disease susceptibility is an important goal in
human genetics. New chip-based technologies are
available that facilitate the measurement of thousands
of DNA sequence variations across the human genome.
Biologically-inspired stochastic search algorithms are
expected to play an important role in the analysis of
these high-dimensional datasets. We simulated datasets
with up to 6000 attributes using two different genetic
models and statistically compared the performance of
grammatical evolution, grammatical swarm, and random
search for building symbolic discriminant functions. We
found no statistical difference among search algorithms
within this specific domain.},
organisation = {IEEE Computational Intelligence Society, Institution
of Electrical Engineers (IEE), Evolutionary Programming
Society (EPS)}, publisher_address = {445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
08855-1331, USA}, isbn = {0-7803-9363-5}, notes = {CEC2005 - A joint meeting of the IEEE, the IEE, and
the EPS.
also appears at pages 676-682},
keywords = {PSO, algorithms, evolution genetic grammatical programming, }
}
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