Abstract
Lighting Standard in work spaces establish a range between a minimal and a maximum level of luminance depending of the task to provide visual comfort. In the state of the art, researches had been focusing to offer the adequate level of luminance just to a single user through the control of the artificial lighting systems using intelligent algorithms, without taking in account of daylight sources that can reduce energy costs. Nevertheless, an intelligent system has more than one user and a shared lighting system, there may be conflicts between users and their different activities, preferences, profiles and priorities, therefore a new approach is required. In this work, a novel methodology based on Genetic Algorithms is proposed, focusing on lights and blinds management of a multi-user scenario and it is presented. It is concentrated to find optimal configurations in energy savings, visual comfort, and conflict resolution between users based on Genetic Algorithms. Finally, the results of our proposal methodology are showed and discussed.
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Romero-Rodríguez, W.J.G., Baltazar, R., Carpio Valadez, J.M., Puga, H., Mosiño, J.F., Zamudio, V. (2018). A Methodology for Optimization of Visual Comfort of Multi-User Intelligent Systems Based on Genetic Algorithms. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications. Studies in Computational Intelligence, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-71008-2_30
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DOI: https://doi.org/10.1007/978-3-319-71008-2_30
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