… Proper use of these models requires calibration of a number … However, traffic dynamics
also depend on factors that cannot … traffic dynamics models for each possible scenario), traffic …

… traffic conditions via real-time internet congestion maps. … timely estimates and predictions
of traffic conditions. Currently, … exploit the potential of traffic prediction models to develop value…

… traffic prediction model … traffic prediction. The analytical results are verified by numerical
computation and simulations. It is shown that the network traffic prediction result of the model is …

… According to the specific modeling strategy, the state-of-the-art deep learning models can …
time-series models. In this study, we first synthetically review the deep traffic models as well as …

… traffic prediction method considering road traffic parameters. To the best of our knowledge, it
is the first time that network traffic is predicted due to road traffic … of network traffic prediction …

… Abstract: - In the traffic noise investigation framework, the need for a suitable predictive model
is … The traffic noise produced by motor vehicles, as main sources in urban areas, is part of …

… We propose a fuzzy Markov prediction model to estimate the traffic … puts the real-time GPS
data into dynamic traffic prediction. … prediction model and other traditional traffic flow prediction …

… traffic prediction model which plays an important role in network management. This article
discusses past network traffic prediction … used in the model, lists the model parameter structure …

… (hourly) plans and provide prediction information to users. This study aims at the prediction
of the traffic volume based on the … The prediction model is based on artificial neural networks. …

… This paper presents the development and evaluation of short-term traffic prediction models
using unidirectional and bidirectional deep learning long short-term memory (LSTM) neural …