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GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
14 years 2 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
EPS
1998
Springer
13 years 11 months ago
Genetic Programming for Automatic Target Classification and Recognition
We use the genetic programming (GP) paradigm for two tasks. The first task given a GP is the generation of rules for the target / clutter classification of a set of synthetic apert...
Stephen A. Stanhope, Jason M. Daida
GECCO
2007
Springer
141views Optimization» more  GECCO 2007»
14 years 1 months ago
Evolving robust GP solutions for hedge fund stock selection in emerging markets
Abstract Stock selection for hedge fund portfolios is a challenging problem for Genetic Programming (GP) because the markets (the environment in which the GP solution must survive)...
Wei Yan, Christopher D. Clack
GECCO
2008
Springer
129views Optimization» more  GECCO 2008»
13 years 8 months ago
Exploiting the path of least resistance in evolution
Hereditary Repulsion (HR) is a selection method coupled with a fitness constraint that substantially improves the performance and consistency of evolutionary algorithms. This als...
Gearoid Murphy, Conor Ryan
JIKM
2006
136views more  JIKM 2006»
13 years 7 months ago
Decision Support Systems Using Ensemble Genetic Programming
Abstract. This paper proposes a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and an ensemble of ...
Ajith Abraham, Crina Grosan