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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Bibliographic Details
Published in:	Energy (Oxford) Vol. 36; no. 10; pp. 5935 - 5943
Main Authors:	Kusiak, Andrew, Xu, Guanglin, Tang, Fan
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01.10.2011 Elsevier
Subjects:	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 Access:	Get full text
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