… The optimization of these neural networks depends on the … particle swarm optimization
(PSO) to CNN-LSTM network for … The proposed PSO-based CNN-LSTM method explores the …

… convolutional neural network (CNN) that is cascaded with a fully-connected network, to …
Spearman’s rank-order correlation, which serves as input size information for the CNN, was …

… CNN is a class of deep networks and is often used in the recognition of images. It is an …
4.1 Recurrent neural network Recurrent Neural Networks (RNN) are discrete time-dynamic …

… A deep learning neural network model based on LSTM networks and particle swarm
optimization (PSO) is proposed in this paper. The PSO algorithm was used to optimize the LSTM …

… determining the CNN-LSTM hyperparameter values using the … CNN-LSTM network, which
improved the prediction performance of the model for battery life. However, the particle swarm …

… We show the last complete connection layer of CNN and PSO-based CNN-LSTM. We
can … CNN-LSTM is performed better than CNN through Fig. 8. CNN and PSO-based CNN-LSTM …

… how the traditional Convolution Neural Network (CNN) model has … Deep Neural Networks
such as CNN and LSTM have widely … hybrid LSTM network model along with different swarm …

… CNN-LSTM neural networks with particle swarm optimization (PSO) to classify the roles in
RBAC system. Convolutional neural network (CNN) … of the CNN-LSTM network and is robust …

… However, the parameters of the CNN-LSTM network model are difficult to set, usually need
to … Therefore, this study adopts hybrid particle swarm optimization (HPSO) and introduces the …

… A hybrid model of CNN with Long Short-Term Memory (LSTM) detects the unsafe behavior
of workers on the construction site [3]. Many large-scale problems have received substantial …