… CNN-LSTM hybrid neural network The structure of the CNN-LSTM hybrid neural network …
to predict the price of Bitcoin with CNN-LSTM hybrid neural network as the core. Different from …

… architecture for HAR using images and videos, we also decide to use hybrid … hybrid CNNLSTM
model on UCI HAR dataset. In this work, we apply LSTM and hybrid CNN-LSTM networks …

… CNN-LSTM network hybrid model response prediction approach based on the CNN and
the LSTM network … It combines CNN and LSTM network features, and employs quasi-distributed …

… To address above issues, we propose a hybrid prediction approach using 1D CNN and
LSTM. First, we use LSTM to learn the complex nonlinearities within the data. This enables the …

… However, the CNN–LSTM network proposed in this paper increases the convergence
speed and recognition accuracy as the input sequence size increases. This indicates that the …

… HYBRID CNN-LSTM NETWORK LSTM and CNN are both outlined to deliver a high …
CNN-LSTM hybrid network basically comprises of a convolution neural network module, a long short-…

… deep learning models CNN and CNN-LSTM to predict the MI … we have proposed: CNN,
hybrid CNN-LSTM, and ensemble … , data balancing, CNN, and LSTM models. Section 3 explains …

… our proposed hybrid network structure. Hence, it yields the optimum performance for CAD
classification. 3) Comparison with existing approaches: The proposed CNN-LSTM network is …

… In this paper, we propose a water quality prediction model named CNN-LSTM with Attention
… The hybrid model CNN-LSTM is highly capable of resolving nonlinear time series prediction …

… To address this issue, a supervised hybrid network based on … , the LSTM network is
concatenated to the CNN layer. … of the hybrid CNN-LSTM network, a deep DCNN-LSTM structure …