The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.

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Signals with a different harmonic content of the fundamental component are present in any power distribution systems due to large quantity and diversity of nonlinear loads connected. In this case, the identification of these loads is necessary in order to mitigate the harmonic currents. Thus, the proposal of this work consists of using an attribute selector (Wrapper) and intelligent systems (Neural Networks and Neural Fuzzy Systems) as an alternative to traditional systems for identification of harmonic sources (nonlinear loads) connected to the electrical system focusing loads commonly encountered in residential customers. Experimental results will be reported and properly justified in order to validate the methodology presented.Index Terms-Harmonic components, intelligent systems, nonlinear loads, identification of harmonic sources.

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