Comparative Study of BSO and GA for the Optimizing Energy in Ambient Intelligence

One of the concerns of humanity today is developing strategies for saving energy, because we need to reduce energetic costs and promote economical, political and environmental sustainability. As we have mentioned before, in recent times one of the main priorities is energy management. The goal in th...

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Bibliographic Details
Published inAdvances in Soft Computing pp. 177 - 188
Main Authors Romero-Rodríguez, Wendoly J. Gpe, Zamudio Rodríguez, Victor Manuel, Baltazar Flores, Rosario, Sotelo-Figueroa, Marco Aurelio, Alcaraz, Jorge Alberto Soria
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
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Summary:One of the concerns of humanity today is developing strategies for saving energy, because we need to reduce energetic costs and promote economical, political and environmental sustainability. As we have mentioned before, in recent times one of the main priorities is energy management. The goal in this project is to develop a system that will be able to find optimal configurations in energy savings through management light. In this paper a comparison between Genetic Algorithms (GA) and Bee Swarm Optimization (BSO) is made. These two strategies are focus on lights management, as the main scenario, and taking into account the activity of the users, size of area, quantity of lights, and power. It was found that the GA provides an optimal configuration (according to the user’s needs), and this result was consistent with Wilcoxon’s Test.
ISBN:9783642253294
3642253296
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-25330-0_16