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EPS
1998
Springer
14 years 3 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
CEC
2009
IEEE
14 years 5 months ago
Performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on the CEC09 test problems
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
TEC
2008
139views more  TEC 2008»
13 years 10 months ago
Genetic Programming Approaches for Solving Elliptic Partial Differential Equations
In this paper, we propose a technique based on genetic programming (GP) for meshfree solution of elliptic partial differential equations. We employ the least-squares collocation pr...
Andras Sobester, Prasanth B. Nair, Andy J. Keane
GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
14 years 4 months ago
Multipopulation cooperative coevolutionary programming (MCCP) to enhance design innovation
This paper describes the development of an evolutionary algorithm called Multipopulation Cooperative Coevolutionary Programming (MCCP) that extends Genetic Programming (GP) to sea...
Emily M. Zechman, S. Ranji Ranjithan
GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
14 years 5 months ago
An analysis of constructive crossover and selection pressure in genetic programming
A common problem in genetic programming search algorithms is destructive crossover in which the offspring of good parents generally has worse performance than the parents. Design...
Huayang Xie, Mengjie Zhang, Peter Andreae