… models developed for short-term traffic flow prediction, the … (CNN), a long short-term memory
(LSTM) network and a gated … components to which our ensemble model gives more weight. …

… optimization method of ensemble element weight parameters, … in this paper builds an
LSTM-CNN prediction element that can … using a methodology based on autoregressive integrated …

… Sets and LSTM, was proposed for traffic flow prediction [19]. … ensemble rule, a recent study
proposed a weight integration … traffic prediction, especially short-term traffic flow prediction, …

… Lu, “EnLSTM-WPEO: Short-term traffic flow prediction by ensemble LSTM, NNCT weight
integration, and population extremal optimization,” IEEE Trans. Veh. Technol., vol. …

… and an ensemble LSTM-SAEs model to enhance the traffic … constraint theory (NNCT) weight
integration and population … model to perform a short-term 5-min traffic flow prediction. We …

… LSTM (ConV-LSTM) and rules for the ensemble diverse convolutional … utilizing ensemble
learning of the LSTM with no negativity constraint theory and using the integration of weights …

… Memory Neural Network (TGC-LSTM) that learns the … Short-term traffic flow forecasting: An
experimental comparison of … UAV video based on ensemble classifier and optical flow. IEEE …

… We present a novel long short-term memory (LSTM) network … integrated in other spatio-temporal
forecasting applications. … learning rate is 0.1 , the weight regularization penalty is set to …

… learning techniques, Long Short-Term Memory (LSTM), Gated … EnLSTM-WPEO model
based on ensemble learning of LSTM, no negative constraint theory (NNCT) weight integration …

… Chen, Short-term traffic flow prediction with LSTM recurrent neural network, in Proc. 2017
IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 201 7. …