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TNN
2010
171views Management» more  TNN 2010»
15 years 1 months ago
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...
Juan Carlos Fernández Caballero, Francisco ...
CEC
2007
IEEE
15 years 8 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
164
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CEC
2010
IEEE
15 years 7 months ago
Classifier-assisted constrained evolutionary optimization for automated geometry selection of orthodontic retraction spring
In orthodontics, retraction springs made of metallic wires are often used to move a tooth with respect to another by the virtue of the spring back effect. Specially selected form o...
Dudy Lim, Yew-Soon Ong, Rachman Setiawan, Muhammad...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 11 months ago
Evolutionary computation methods for synchronization of effects based operations
Effects based operations (EBO) is a concept based on the premise that a desired strategic outcome can be achieved through synergistic, multiplicative, and cumulative application ...
Jeffrey P. Ridder
ICML
2003
IEEE
15 years 11 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens