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» An evolutionary method for complex-process optimization
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92
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GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
15 years 7 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
108
Voted
GECCO
2006
Springer
172views Optimization» more  GECCO 2006»
15 years 4 months ago
Multi-objective optimisation of the protein-ligand docking problem in drug discovery
The pharmaceutical industry is facing an ever-increasing demand to discover novel drugs that are more effective and safer than existing ones. The industry faces huge problem in im...
A. Oduguwa, A. Tiwari, S. Fiorentino, R. Roy
100
Voted
GECCO
2008
Springer
149views Optimization» more  GECCO 2008»
15 years 1 months ago
Real-time imitation-based adaptation of gaming behaviour in modern computer games
In the course of the recent complexification and sophistication of commercial computer games, the creation of competitive artificial players that are able to behave intelligentl...
Steffen Priesterjahn, Alexander Weimer, Markus Ebe...
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
15 years 1 months ago
Varying portfolio construction of stocks using genetic network programming with control nodes
A new evolutionary method named “Genetic Network Programming with Control Nodes, GNPcn” has been proposed and applied to determine the timing of buying and selling stocks. GNP...
Etsushi Ohkawa, Yan Chen, Shingo Mabu, Kaoru Shima...
115
Voted
CEC
2009
IEEE
15 years 5 months ago
Memetic algorithm with Local search chaining for large scale continuous optimization problems
Abstract— Memetic algorithms arise as very effective algorithms to obtain reliable and high accurate solutions for complex continuous optimization problems. Nowadays, high dimens...
Daniel Molina, Manuel Lozano, Francisco Herrera