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» Combining genetic algorithms with squeaky-wheel optimization
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GECCO
2004
Springer
132views Optimization» more  GECCO 2004»
14 years 1 months ago
Robust and Efficient Genetic Algorithms with Hierarchical Niching and a Sustainable Evolutionary Computation Model
This paper proposes a new niching method named hierarchical niching, which combines spatial niching in search space and a continuous temporal niching concept. The method is natural...
Jianjun Hu, Erik D. Goodman
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
13 years 12 months ago
Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed using a hybrid neural networks training algorithm. This algorithm combines genetic algorithm...
Adam V. Adamopoulos, Efstratios F. Georgopoulos, S...
ICANNGA
2007
Springer
100views Algorithms» more  ICANNGA 2007»
14 years 1 months ago
Genetic-Greedy Hybrid Approach for Topological Active Nets Optimization
In this paper we propose a genetic and greedy algorithm combination for the optimization of the Topological Active Nets (TAN) model. This is a deformable model used for image segme...
José Santos, Óscar Ibáñ...
GECCO
2010
Springer
232views Optimization» more  GECCO 2010»
13 years 8 months ago
Genetic algorithms for automatic classification of moving objects
This paper presents an integrated approach, combining a state-of-the-art commercial object detection system and genetic algorithms (GA)-based learning for automatic object classif...
Omid David-Tabibi, Nathan S. Netanyahu, Yoav Rosen...
ICDAR
2003
IEEE
14 years 29 days ago
Comparison of Genetic Algorithm and Sequential Search Methods for Classifier Subset Selection
Classifier subset selection (CSS) from a large ensemble is an effective way to design multiple classifier systems (MCSs). Given a validation dataset and a selection criterion, the...
Hongwei Hao, Cheng-Lin Liu, Hiroshi Sako