… Classifying states of traffic situations as peak and non-peak periods, we aim to analyze
which model is more suitable or applicable in each period. From a practical perspective, we …

… relatively stable traffic inevitably … of forecasts in non-peak hours is fundamental to traffic
prediction. And the LS-SVMs method is proposed to predict and analyze traffic status in non-peak …

… -day traffic flow using a forecasting horizon of 1 h 15 min with a 15-min step. Thus, every 15
min, the traffic … length and peak volumes of predicted traffic flows, make it difficult to find two …

… , we extend the analysis here to consider how and why forecast accuracy changes over
time, to … , but after VMT per capita peaks, the opposite is true. This relationship suggests that …

… forecast traffic are analysed and discussed. An elementary approach is to develop heuristics
based on the statistical analysis … a traffic forecast the standard deviations of the peaks are …

… of traffic flow time series. To solve the problem, this paper relies on deep learning (DL) to
forecast traffic flow through time series analysis… accurately forecast the traffic flow in peak hours. …

… similar trends on typical workdays with morning and afternoon peaks during the commuting
periods, a lower traffic rate at noon, and a flat flow rate at midnight. The field observations of …

… The predictable component of variation can be simply the widely known and accepted
regular weekday or workday patterns of the peak or offpeak traffic, the lower demand levels …

… Short-term traffic forecasting is an important tool in following the evolution of traffic … hours,
it can be concluded that the MAPE values of the forecasts are less during peak hours. These …

… has left traffic agencies in dire need of a robust method for analyzing and forecasting traffic.
… -free, data-driven approach for analyzing and forecasting traffic dynamics. By obtaining a …