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GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 2 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
ICPR
2008
IEEE
15 years 11 months ago
Computer graphics identification using genetic algorithm
This paper proposes the use of genetic algorithm to select an optimal feature set for distinguishing computer graphics from digital photographic images. Our previously developed a...
Wen Chen, Yun Q. Shi, Guorong Xuan, Wei Su
GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
15 years 10 months ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 10 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 10 months ago
Exploring extended particle swarms: a genetic programming approach
Particle Swarm Optimisation (PSO) uses a population of particles that fly over the fitness landscape in search of an optimal solution. The particles are controlled by forces tha...
Riccardo Poli, Cecilia Di Chio, William B. Langdon