Traffic Control on Cruise Ships for Autonomous Vehicles Applying Artificial Neural Network

The Artificial Neural Networks, from their origin, are oriented to solve problems in the same way as the human brain would. They use real data for their training and, through various algorithms, they seek to reach an optimal solution. In the present article the design of a Neuronal Artificial Network of multilayer perceptron type (PMC) for the control of autonomous vehicles in cruises is proposed. The training of the network was carried out applying Hyperbolic Tangent Sigmoid, Hyperbolic Log-Sigmoid and finally the linear functions.