A Filling Method Based on K-Singular Value Decomposition (K-SVD) for Missing and Abnormal Energy Consumption Data of Buildings

A Filling Method Based on K-Singular Value Decomposition (K-SVD) for Missing and Abnormal Energy Consumption Data of Buildings

Massive data can be collected from meters to analyze the energy use behavior and detect the operation problems of buildings. However, missing and abnormal data often occur for the raw data. Effective data filling and smoothing methods are required to improve data quality before conducting the analys...

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Bibliographic Details
Main Authors: Lihong Su, Manjia Liu, Zaixun Ling, Wenjie Gang, Chong Zhang, Ying Zhang, Xiuxia Hao
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Buildings
Subjects:
K-SVD
data filling
missing data
data pre-processing
building energy
Online Access:https://www.mdpi.com/2075-5309/14/3/696

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