%0 Journal Article
%T Improving the Classification Efficiency of an ANN Utilizing a New Training Methodology
%A Ioannis E. Livieris
%J -
%D 2019
%R https://doi.org/10.3390/informatics6010001
%X Abstract In this work, a new approach for training artificial neural networks is presented which utilises techniques for solving the constraint optimisation problem. More specifically, this study converts the training of a neural network into a constraint optimisation problem. Furthermore, we propose a new neural network training algorithm based on the L-BFGS-B method. Our numerical experiments illustrate the classification efficiency of the proposed algorithm and of our proposed methodology, leading to more efficient, stable and robust predictive models. View Full-Tex
%K artificial neural networks
%K constrained optimisation
%K L-BFGS-B
%K accuracy
%U https://www.mdpi.com/2227-9709/6/1/1