… In this paper, we propose a CNN-LSTM neural network that can extract spatial and …
CNN-LSTM neural network combining CNN and LSTM to predict residential energy consumption…

… for stably predicting electric energy consumption on IHEPC dataset. The CNN-LSTM method
in … performance for IHEPC dataset compared with Linear Regression, LSTM approaches. …

… of CNN kernels, the number of hidden units in LSTM and the … layer of CNN-LSTM model
for electricity energy consumption … the CNN-LSTM model for electric energy consumption …

… Inspired by this, we combine a CNN with M-BDLSTM in the proposed method as a series
connection network to predict energy consumption. This network extracts and learns complex …

… on a real-world household energy consumption dataset collected by the ‘UK-… (LSTM)
neural network and convolutional neural network combining long short term memory (CNN-LSTM), …

… mechanism because of the application of historical energy data to predict energy consumption
in the future, and (b) it cannot make full use of all information, because only historical …

… of energy consumption in household power consumption dataset. We use the CNN-LSTM …
data changes to predict power consumption through CNN-LSTM internal analysis. We also …

… presents k CNN-LSTM, a deep learning framework that operates on the energy consumption
data recorded at predefined intervals to provide accurate building energy consumption …

… energy consumption forecasting using multi-variables as input. Hu et al. [26] also applied
CNN–LSTM … proposed a hybrid of CNN–LSTM to predict power consumption by using raw time …

… -term power consumption forecasting based on a cascading CNN-LSTM structure with DWT
… Rho, and SW Baik, ‘‘Shortterm prediction of residential power energy consumption via CNN …