A metamodel-based multi-objective optimization method to balance thermal comfort and energy efficiency in a campus gymnasium

•A method for the metamodel-based multi-objective optimization of large space building, taking advantage of high performance computing, was developed.•An actual campus gymnasium in Qingdao, China was the case study.•The normalized degree-hours for naturally-ventilated seasons and the energy consumpt...

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Veröffentlicht in:	Energy and buildings Jg. 253; S. 111513
Hauptverfasser:	Yue, Naihua, Li, Lingling, Morandi, Alessandro, Zhao, Yang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Lausanne Elsevier B.V 15.12.2021 Elsevier BV
Schlagworte:	Absorptance Absorptivity Air conditioning Algorithms Artificial neural networks Building design Configuration management Cooling Design factors Design optimization Energy consumption Energy efficiency External walls Genetic algorithms Green buildings Gymnasium Heating Hypercubes Metamodels MLPANN Multi-objective optimization Multilayers Multiple objective analysis Neural networks NSGA-II Pareto optimization Principal components analysis Public buildings Sorting algorithms Thermal comfort Ventilation NSGA-II Energy consumption MLPANN Thermal comfort Multi-objective optimization Gymnasium
ISSN:	0378-7788, 1872-6178
Online-Zugang:	Volltext
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