Aug 5, 2015 · This method is applied to the traffic flow time series to analyze and compare the predicting performance of the predicting model based on the ...

This method is applied to the traffic flow time series to analyze and compare the predicting performance of the predicting model based on the neural network ...

Aug 5, 2015 · work and fuzzy system, this paper makes a further research on the dynamic fuzzy neural networks (D-FNN) traffic flow prediction. Instead of ...

[26, 27] Yang et al. [28] selected the appropriate wavelet basis to decompose and reconstruct the traffic flow data. The results showed that prediction effect ...

Nov 14, 2022 · Therefore, this paper proposes a novel hybrid model called FGRU combining a fuzzy inference system (FIS) and a gated recurrent unit (GRU) neural ...

Apr 17, 2023 · The goal of traffic flow prediction is to estimate future traffic conditions of a transportation network based on historical observations. The ...

Bibliographic details on Research on prediction of traffic flow based on dynamic fuzzy neural networks.

This method is applied to the traffic flow time series to analyze and compare the predicting performance of the predicting model based on the neural network ...

Jun 5, 2024 · This paper makes a preliminary attempt to change scenario by using artificial neural networks (ANNs) to model the past historical data. It aims ...

This study develops a traffic flow dependency and dynamics based deep learning aided approach (TD2-DL), which predict network-wide high resolution traffic speed ...