Neural network based approach for automotive brake light parameter estimation

  • Authors:

  • Antonio Vanderlei Ortega;Ivan Nunes da Silva

  • Affiliations:

  • Department of Electrical Engineering, University of São Paulo, São Carlos, SP, Brazil;Department of Electrical Engineering, University of São Paulo, São Carlos, SP, Brazil

  • Venue:
  • ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

The advantages offered by the electronic component LED (Light Emitting Diode) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. Such technique can be used to design any automotive device that uses groups of SMD LEDs. Results of industrial applications, using SMD LED, are presented to validate the proposed technique.