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.
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Ortega, A.V., da Silva, I.N. (2012). Neural Network Based Approach for Automotive Brake Light Parameter Estimation. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34478-7_74
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DOI: https://doi.org/10.1007/978-3-642-34478-7_74
Publisher Name: Springer, Berlin, Heidelberg
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