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» On the practical genetic algorithms
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GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
15 years 10 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
GECCO
2008
Springer
154views Optimization» more  GECCO 2008»
15 years 8 months ago
Automated shape composition based on cell biology and distributed genetic programming
Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell i...
Linge Bai, Manolya Eyiyurekli, David E. Breen
GECCO
2007
Springer
165views Optimization» more  GECCO 2007»
16 years 1 months ago
Peptide detectability following ESI mass spectrometry: prediction using genetic programming
The accurate quantification of proteins is important in several areas of cell biology, biotechnology and medicine. Both relative and absolute quantification of proteins is often d...
David C. Wedge, Simon J. Gaskell, Simon J. Hubbard...
BMCBI
2010
208views more  BMCBI 2010»
15 years 7 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
16 years 1 months ago
Soft memory for stock market analysis using linear and developmental genetic programming
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...
Garnett Carl Wilson, Wolfgang Banzhaf