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» Fast convergence in evolutionary models: A Lyapunov approach
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TEC
2002
161views more  TEC 2002»
13 years 6 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...
TMI
2002
248views more  TMI 2002»
13 years 6 months ago
Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Alain Pitiot, Arthur W. Toga, Paul M. Thompson
CEC
2008
IEEE
14 years 1 months ago
Auto-tuning fuzzy granulation for evolutionary optimization
—Much of the computational complexity in employing evolutionary algorithms as optimization tool is due to the fitness function evaluation that may either not exist or be computat...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
GECCO
2009
Springer
144views Optimization» more  GECCO 2009»
14 years 1 months ago
Cheating for problem solving: a genetic algorithm with social interactions
We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary...
Rafael Lahoz-Beltra, Gabriela Ochoa, Uwe Aickelin
ICTAI
2005
IEEE
14 years 8 days ago
Hybrid Learning Neuro-Fuzzy Approach for Complex Modeling Using Asymmetric Fuzzy Sets
A hybrid learning neuro-fuzzy system with asymmetric fuzzy sets (HLNFS-A) is proposed in this paper. The learning methods of random optimization (RO) and least square estimation (...
Chunshien Li, Kuo-Hsiang Cheng, Jiann-Der Lee