Linear model optimizer vs Neural Networks: A comparison for improving the quality and saving of LED-Lighting control systems | IEEE Conference Publication | IEEE Xplore

Linear model optimizer vs Neural Networks: A comparison for improving the quality and saving of LED-Lighting control systems


Abstract:

Lighting systems represents about 38% of the total energy consumption in office buildings, however, a great amount of this energy is wasted because luminaires keep workin...Show More

Abstract:

Lighting systems represents about 38% of the total energy consumption in office buildings, however, a great amount of this energy is wasted because luminaires keep working at its maximum power even when just a single person is present. In order to improve the performance of LED-Lighting control systems, we propose a linear model that considers the luminaire's influence on its neighborhood and takes into account visual comfort and energy consumption. The proposed linear model was contrasted against two Neural Network configurations that were trained to find the best dimming levels. Our experiments demonstrate that a linear optimizer applied to our proposed linear model have a better performance than any of the two tested neural networks.
Date of Conference: 04-08 December 2016
Date Added to IEEE Xplore: 24 April 2017
ISBN Information:
Conference Location: Cancun, Mexico

References

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