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» Generalized crowding for genetic algorithms
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133
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GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
15 years 3 months ago
Evolving recurrent models using linear GP
Turing complete Genetic Programming (GP) models introduce the concept of internal state, and therefore have the capacity for identifying interesting temporal properties. Surprisin...
Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywoo...
GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
15 years 1 months ago
Behavioural GP diversity for dynamic environments: an application in hedge fund investment
We present a new mechanism for preserving phenotypic behavioural diversity in a Genetic Programming application for hedge fund portfolio optimization, and provide experimental res...
Wei Yan, Christopher D. Clack
IJCAI
1997
14 years 11 months ago
Evolvable Hardware for Generalized Neural Networks
This paper describes an evolvable hardware (EHW) system for generalized neural network learning. We have developed an ASIC VLSI chip, which is a building block to configure a scal...
Masahiro Murakawa, Shuji Yoshizawa, Isamu Kajitani...
80
Voted
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 4 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen
GECCO
2005
Springer
209views Optimization» more  GECCO 2005»
15 years 3 months ago
Genetic algorithm optimization of superresolution parameters
Superresolution is the process of producing a high resolution image from a collection of low resolution images. This process has potential application in a wide spectrum of fields...
Barry Ahrens