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» Solving iterated functions using genetic programming
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GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
14 years 5 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
CEC
2009
IEEE
14 years 2 months ago
Using genetic programming to obtain implicit diversity
—When performing predictive data mining, the use of ensembles is known to increase prediction accuracy, compared to single models. To obtain this higher accuracy, ensembles shoul...
Ulf Johansson, Cecilia Sönströd, Tuve L&...
GECCO
2007
Springer
165views Optimization» more  GECCO 2007»
14 years 5 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...
EPS
1998
Springer
14 years 2 months ago
A Genetic Programming Methodology for Missile Countermeasures Optimization Under Uncertainty
: This paper describes a new methodology for using genetic programming to solve the missile countermeasures optimization problem. The resulting system evolves programs that combine...
Frank W. Moore, Oscar N. Garcia
FLAIRS
2004
14 years 8 days ago
Iterative Improvement of Neural Classifiers
A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...