International Journal of Advanced Networking and Applications

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


Affiliations
1 Department of Systems and Computation, Villahermosa Institute of Technology, Mexico
2 Department of Industrial Engineer, Villahermosa Institute of Technology, Mexico
3 Department of Telecom, PEMEX, Mexico
 

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.

Keywords

Neural Network, Robotics, Multilayer Perceptron, Automation.
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  • Traffic Control on Cruise Ships for Autonomous Vehicles Applying Artificial Neural Network

Abstract Views: 231  |  PDF Views: 0

Authors

Ezequiel Gomez Dominguez
Department of Systems and Computation, Villahermosa Institute of Technology, Mexico
Jorge Cein Villanueva Guzman
Department of Systems and Computation, Villahermosa Institute of Technology, Mexico
Victor Manuel Arias Peregrino
Department of Systems and Computation, Villahermosa Institute of Technology, Mexico
Julio Cesar Romellon Cerino
Department of Industrial Engineer, Villahermosa Institute of Technology, Mexico
Juan Carlos Arias Peregrino
Department of Telecom, PEMEX, Mexico

Abstract


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.

Keywords


Neural Network, Robotics, Multilayer Perceptron, Automation.

References