TRAFFIC flowCOPULA functionsTIME series analysisMETROPOLITAN areasEXTREME value theoryTime series of traffic flows, extracted from mobile phone origin鈥揹estination data, are employed for monitoring people crowding and mobility in areas subject to flooding risk. By applying a vector autoregressive model ...
In operating a real-time, traffic-responsive control system, such as freeway ramp control system, most of the decisions made by the system will depend on i... N Nihan,K Knutson 被引量: 0发表: 1993年 Traffic analysis traffic analysis: box-jenkins time series analysis models for freeway tr...
incomplete and may cause out of order.The model for filling time series data of traffic flow based on LS-SVM is proposed in this paper,missing data can be filled by using traffic flow historical data.The simulation results show that LS-SVM have better generalization ability and strong ...
deep-learningtoolkittrafficetamap-matchingrepresentation-learningon-demand-servicespatio-temporaltraffic-predictiontrajectory-predictiontime-series-predictionspatio-temporal-predictiontraffic-flow-predictionpytorch-implementationod-matrixtraffic-forecastingestimated-time-of-arrivaltraffic-accident-predictiontraffic-speed-predic...
To further improve the accuracy of short-term traffic flow prediction, a short-term traffic flow prediction model based on traffic flow time series analysis, and an improved long short-term memory network (LSTM) is proposed. First, perform time series analysis on traffic flow data and perform ...
The seasonal autoregressive integrated moving average (SARIMA) model is one of the popular univariate time-series models in the field of short-term traffic flow forecasting. The parameters of the SARIMA model are commonly estimated using classical (maximum likelihood estimate and/or least-squares estim...
of the traffic flow series. Moreover, the investigation into the effects of outliers on the forecasting system structure showed a significant connection between the outliers and the forecasting system parameters changes. General conclusions are provided concerning the analyses with future work recommended ...
Traffic Flow Analysis: Urban traffic and public transportation systems exhibit complex time series patterns due to varying factors like time of day, weather, and events. Unsupervised models can identify irregular traffic patterns or disruptions. Supply Chain and Inventory Management: In logistics, the ...
In order to obtain insight into the nature of the dynamics, we apply the nonlinear time series analysis approach to study the characteristic behavior of traffic flow at low and intermediate density values. A procedure called "embedding scheme" has been used to reconstruct the representation of the...
In order to improve the effect of short-term traffic flow prediction, this paper presents a short-term traffic flow multistep prediction method based on similarity search of time series. Firstly, the landmark model is used to represent time series of traffic flow data. Then the input data of...