A Lamarckian Model Combining Levenberg-marquardt Algorithm and a Genetic Algorithm

We review the integration between the genetic and evolutionary techniques with artificial neural networks. A Lamarckian model is proposed based on genetic algorithms and artificial neural networks. The genetic algorithm evolves the population while the artificial neural network performs the learning process. The direct encoding scheme was used. This model was submitted to several data sets and provided good results, exhibiting superior robustness when compared with the LevenbergMarquardt and the Scaled Conjugate Gradient algorithms. It also achieved the best solutions in the regression problems.