Self-configuring Two Types of Neural Networks by MPCA
Juliana Aparecida Anochi, Haroldo Fraga de Campos Velho, Helaine C. M. Furtado, Eduardo Fávero Pacheco da Luz · Journal of Mechanics Engineering and Automation · 2015
ANN (artificial neural network) is a technique successfully employed in many applications on several research fields.An appropriate configuration for neural networks is a tedious task, and it often requires the knowledge of an expert on the application.In this paper, a technique for automatic configuration for two types of neural networks is presented.The multilayer perceptron and recurrent Elman are the neural networks used here.The determination of optimal parameters for the neural network is formulated as an optimization problem, solved with the use of meta-heuristic MPCA (multiple particle collision algorithm).The self-configuring networks are applied to perform data assimilation.