Tuning Artificial Neural Networks Parameters Using an Evolutionary Algorithm

This paper describes a method to automatically tuning artificial neural networks parameters for a specific problem using an evolutionary algorithm. The method employs an evolutionary search to perform simultaneous tuning of initial weights, transfer functions, architectures and learning rules (learning algorithms parameters). Experiments were performed and the results demonstrate that the method in a shorter time of search, is able to find efficient networks with satisfactory generalization capabilities.