… Furthermore, we propose the methodology of a hybrid prediction model combining a widely
used ARIMA model from the statistical category with SVM from the machine learning category…

… should have the ability to capture prominent traffic … traffic prediction model based on
non-linear time series ARIMA/GARCH. This model combines linear time series ARIMA model …

… Here, we intend to model the relation of the traffic value of L11 to the other directly connected
segments, that is, L12 and L16. Regarding commute hours, even though L11 and L16 …

… traffic noise is the most pervasive source of ambient outdoor noise pollution in Europe. Traffic
noise prediction models … This paper compares three such models: the European standard, …

… The goal of the volume prediction model is to be able to predict the number of packets and
bytes we can expect to see in a future 5 second time window. To formally state the volume …

… for modeling traffic flow in this paper. A comprehensive review of the different approaches and
applications of ANNs in traffic prediction … incorporated in the prediction model accordingly. …

… with ResNet to optimize the overall model, reduce the occurrence of gradient … prediction of
traffic flow. According g to the experimental results, the combined traffic flow prediction model …

… cellular traffic prediction models. This paper proposes a LSTM based cellular traffic prediction
model … We have compared the LSTM based prediction with ARIMA model and vanilla Feed…

… Inspired by this study, this paper also uses the decomposition prediction model to study
the prediction of network traffic. The difference from this study is that this paper uses LMD …

… Surveys conducted in many countries have shown that traffic noise is … traffic noise prediction
model according to the traffic and environmental conditions. Traffic noise prediction models …