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Dec 1, 2023 ， [19] proposed a bi-directional imputation approach using a Long Short-term Memory (LSTM) network. They test their model with two missing mechanisms: random and ...
Jun 21, 2024 ， Long-term missing value imputation for time series data using deep neural networks ... Handling bad or missing smart meter data through advanced data imputation.
Mar 23, 2024 ， In (Fei et al., 2022) neural network model based on Neural Architecture Search (NAS) is developed to analyze and detect electricity theft in missing value ...
Jan 19, 2024 ， The new reliable data are imputed (reinserted) through the principled imputation techniques, which replace the missing value indirectly. The observed data ...
Mar 1, 2024 ， The research aims to present a unique hybrid model, merging. Gradient Boosting Machine (GBM) and Long Short-Term. Memory (LSTM) networks, to overcome existing ...
Mar 11, 2024 ， Some researchers have imputed missing values with the mean values of relevant data [118, 119, 120] . The authors in [121] concluded that linear and spline ...
Nov 1, 2023 ， Long short-term memory NN is utilized along with the concept drift process to develop contextual anomaly detection technique as proposed in [155]. Regarding ...
Dec 22, 2023 ， This paper presents a comprehensive review of super-resolution methods for smart meter data analysis. Smart meters provide valuable insights into household ...
Jan 31, 2024 ， The combination of convolutional neural network (CNN) and LSTM proves to be useful in constructing forecast-assisted methods to identify anomalies related to ...
May 13, 2024 ， The study focuses on implementing and evaluating energy consumption prediction models using algorithms like long short-term memory (LSTM), random forest, and.