… on the short-term traffic flow prediction problem based on realworld traffic data as … traffic
flows1). In this paper, we focus on short-term traffic flow prediction problem which aims to predict …

… , network design, short and long-term resource allocation, traffic (re)-… of prediction methods,
based on long and short term’s periods, are typically considered. Long-term traffic prediction …

… cant part of smart city, and short-term traffic flow prediction plays an important role in
intelligent transportation management and route guidance. A number of models and algorithms …

… To solve the challenging task of one step long-term traffic prediction, we propose the multiple
time-intervals feature learning network (MTIFLN) that integrates multiple bidirectional …

… a long-term traffic prediction framework that integrates an RNN-LF based on weather
information, historical traffic … is useful for both short-term and long-term traffic condition prediction. …

… In this paper, we study the mobile traffic of an LTE base station and we design a system
for the traffic prediction using Recurrent Neural Networks. The mobile traffic information is …

… We compare the performance of 60 min and 90 min traffic predictions with different adjacency
matrices, and results are shown in Table I. STGCN denotes the default STGCN model with …

… Traffic prediction is required for a number of different time scales, including long term planning
… of service of the existing traffic [l], [2], and finally the dynamic prediction that is required for …

… Our study evaluates the traffic prediction over a (long) set of highway sections. In this case,
the traffic data has a single spatial dimension. The convolution filters of the CNN+LSTM …

… In this work, we perform the IoT traffic prediction using deep neural network learning (DNN)
with the LSTM network. we predict the IoT traffic with time series prediction. The prediction …