… a hybrid deep learning method by combining the convolutional neural network (CNN) and
long short-term memory (LSTM) network … input into the corresponding CNN-LSTM for voltage …

… In this study, a hybrid CNN-LSTM model was developed on a … is that the proposed CNN-LSTM
model outperformed them all… show that, while standalone CNN and LSTM models provide …

… This paper presents a novel hybrid cross-channel-communication-enabled CNN-LSTM …
Our proposed model is a hybrid framework which a the combination of CNN and LSTM models. …

… To this end, we combine a one-dimensional CNN and an LSTM in a new model: CNN-LSTM.
The CNN-LSTM model consists of (1) a one-dimensional convolutional layer, (2) an LSTM …

… Inspired by the CNN-LSTM scheme, this paper proposes a novel hybrid neural … The
hybrid neural networks proposed in this paper use CNN and LSTM to extract short-term local …

… The proposed hybrid network can predict regardless of the source of data with a drastic
improvement in hospital-specific cases, where it shows an 11.5 % increase in the prediction …

… on CNN and LSTM. This method uses CNN to analyze the spatial correlation of different
regions, and captures the time series characteristics of power generation data through LSTM. It …

… , we suggest a hybrid method, named the CNN-LSTM-DNN, … In this paper, a hybrid
CNN-LSTM-DNN algorithm is sug… volutional Neural Networks (CNNs), Deep Neural Networks …

… neural network-long short-term memory (CNN-LSTM) … made by an aggregate network based
on the simultaneously … ) by applying a hybrid CNN-LSTM model and aggregate network to …

… then uses the proposed hybrid CNN-LSTM model [12] … hybrid CNN-LSTM model is proposed
for the actuator fault diagnosis in six-rotor UAVs. To begin with, we design a neural network …