Power consumption minimization by distributive particle swarm optimization for luminance control and its parallel implementations

•Luminance control is formalized as a constrained search problem.•Both power consumption minimization and sufficient illuminance are considered.•A distributive PSO-based algorithm is developed to do an effective search.•Parallel implementations in GPU and Hadoop MapReduce are developed.•The develope...

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Veröffentlicht in:	Expert systems with applications Jg. 96; S. 479 - 491
Hauptverfasser:	Liao, Chih-Lun, Lee, Shie-Jue, Chiou, Yu-Shu, Lee, Ching-Ran, Lee, Chie-Hong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 15.04.2018 Elsevier BV
Schlagworte:	Computer simulation CUDA Electricity Energy conservation Energy consumption GPU Hadoop Illuminance Industrial plants Lighting Luminance MapReduce Parallel algorithm Parallel processing Particle swarm optimization Power consumption Real time Working conditions Workshops CUDA Parallel algorithm Energy conservation Hadoop Particle swarm optimization GPU MapReduce
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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