In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
Local genetic algorithms have been designed with the aim of providing effective intensification. One of their most outstanding features is that they may help classical local searc...
In this work we examined the performance of two evolutionary algorithms, a genetic algorithm (GA) and particle swarm optimization (PSO), in the estimation of the parameters of a mo...
Dulce Calcada, Agostinho Rosa, Luis C. Duarte, Vit...
—Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational step...
Recent research into single–objective continuous Estimation– of–Distribution Algorithms (EDAs) has shown that when maximum–likelihood estimations are used for parametric d...