Evaluating the impact of data preprocessing to develop a robust MEP-based forecasting model for building integrated with PCM

Data quality is a crucial aspect to accurately predict the energy use of buildings utilizing machine learning methods. Data preprocessing can ensure data quality when a database does not match the criteria for evolving a robust prediction model. Regarding phase change material (PCM)-incorporated bui...

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Veröffentlicht in:	Energy (Oxford) Jg. 324; S. 135763
Hauptverfasser:	Nazir, Kashif, Memon, Shazim Ali
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.06.2025
Schlagworte:	Data preprocessing data quality energy Energy consumption Model interpretability model validation Multi-expression programming Phase change material phase transition prediction Energy consumption Phase change material Model interpretability Multi-expression programming Data preprocessing
ISSN:	0360-5442
Online-Zugang:	Volltext
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