Optimization of an HVAC system with a strength multi-objective particle-swarm algorithm

A data-driven approach for the optimization of a heating, ventilation, and air conditioning (HVAC) system in an office building is presented. A neural network (NN) algorithm is used to build a predictive model since it outperformed five other algorithms investigated in this paper. The NN-derived pre...

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Veröffentlicht in:	Energy (Oxford) Jg. 36; H. 10; S. 5935 - 5943
Hauptverfasser:	Kusiak, Andrew, Xu, Guanglin, Tang, Fan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ltd 01.10.2011 Elsevier
Schlagworte:	air conditioning Algorithms Applied sciences Construction Energy Energy consumption Evolutionary computation Exact sciences and technology heat humidity HVAC Mathematical models Neural networks Neutral network Optimization Strength Strength multi-objective particle-swarm algorithm temperature Thermal comfort Neutral network HVAC Strength multi-objective particle-swarm algorithm Optimization Evolutionary computation
ISSN:	0360-5442
Online-Zugang:	Volltext
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