Estimation of Prediction Intervals of Neural Network Models by a Multi-objective Genetic Algorithm
Résumé
In this work, we implement a multi-objective genetic algorithm (namely, non-dominated sorting genetic algorithm-II (NSGA-II)) to find the parameters of an ANN which provides in output the lower and upper bounds of the prediction intervals of a quantity of interest. We apply the proposed method on a synthetic case study of literature.