Comparative analysis of adjustment in artificial neural networks training using open nn and alglib libraries

Abstract

In the last decades, there have been a considerable amount of innovations in the development of applications and the scope of artificial neural networks, and likewise the technological development in computer science. These improvements have had a direct effect in the number of publications on applications, in diverse areas of knowledge, based on this artificial intelligence method. Until now, the adequacy and applicability of free software tools to facilitate the implementation and the quality of results is still under discussion. In this context, this work presents a comparative analysis of such applications using libraries ALGLIB and Open NN, oriented to training and reproduction of artificial neural networks. Also, we propose an evaluation of the results obtained from the levels of correlation between the output values for trained networks and a set of data for simulated training.