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» Evolutionary multiobjective optimization
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GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
15 years 8 months ago
Neural network ensembles for time series forecasting
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
Victor M. Landassuri-Moreno, John A. Bullinaria
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
15 years 5 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
GECCO
2010
Springer
192views Optimization» more  GECCO 2010»
15 years 4 months ago
Resource abundance promotes the evolution of public goods cooperation
Understanding the evolution of cooperation as part of an evolutionary stable strategy (ESS) is a difficult problem that has been the focus of much work. The associated costs of co...
Brian D. Connelly, Benjamin E. Beckmann, Philip K....
GECCO
2008
Springer
152views Optimization» more  GECCO 2008»
15 years 2 months ago
Combatting financial fraud: a coevolutionary anomaly detection approach
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
Shelly Xiaonan Wu, Wolfgang Banzhaf
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
15 years 7 months ago
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
Oliver Kramer, Bartek Gloger, Andreas Goebels