Towards missing electric power data imputation for energy management systems-Reference-Cited by-同舟云学术

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Towards missing electric power data imputation for energy management systems

Published:2021-07 Issue: Volume:174 Page:114743
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Wang Ming-Chang,Tsai Chih-Fong,Lin Wei-Chao

Funder

Ministry of Science and Technology, Taiwan

Chang Gung Memorial Hospital, Linkou

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference47 articles.

1. Missing data imputation of high-resolution temporal climate time series data;Afrifa‐Yamoah;Meteorological Applications,2020

2. Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia;Al-Musaylh;Advanced Engineering Informatics,2018

3. Hot weather and residential hourly electricity demand in Italy;Alberini;Energy,2019

4. A bagging algorithm for the imputation of missing values in time series;Andiojaya;Expert Systems with Applications,2019

5. Disaggregating time series on multiple criteria for robust forecasting: The case of long-term electricity demand in Greece;Angelopoulos;European Journal of Operational Research,2019

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3. An L1-and-L2-regularized nonnegative tensor factorization for power load monitoring data imputation;Frontiers in Energy Research;2024-07-26

4. Robust multi-scale time series prediction for building carbon emissions with explainable deep learning;Energy and Buildings;2024-06

5. Handling missing values and imbalanced classes in machine learning to predict consumer preference: Demonstrations and comparisons to prominent methods;Expert Systems with Applications;2024-03

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