This paper presents a multiobjective evolutionary algorithm to optimize radial basis function
neural networks (RBFNNs) in order to approach target functions from a set of input-output …

Interest in hybrid methods that combine artificial neural networks and evolutionary
algorithms has grown in the last few years, due to their robustness and ability to design …

In this paper we present a comparative study of several methods that combine evolutionary
algorithms and local search to optimize multilayer perceptrons: A method that optimizes the …

The daunting and challenging tasks of specifying the optimal network architecture and its
parameters are still a major area of research in the field of Machine Learning (ML) till date …

Although a great amount of algorithms have been devised to train the weights of a neural
network for a fixed topology, most of them are hillclimbing procedures, which usually fall in a …

Current information systems used for data collection and to generate information on the state
of the roads have two drawbacks: the first is that they have no ability to identify target …

Hybrid neuro-evolutionary algorithms may be inspired on Darwinian or Lamarckian evolu-
tion. In the case of Darwinian evolution, the Baldwin effect, that is, the progressive …

Software visualization is an area of computer science devoted to supporting the
understanding and effective use of algorithms. The application of software visualization to …

Este artículo presenta la abstracción de Objetos Evolutivos Paralelos (OEP), un nuevo
framework en computación evolutiva que intenta unificar todos los paradigmas actuales. Al …

Dados los beneficios de un sistema de información sobre el estado del tráfico y de
predicción del uso de la red viaria por parte de los vehıculos, se plantea el desarrollo de un …