Results 11 to 20 of about 4,103,347 (253)
Hybrid Extreme Learning for Reliable Short-Term Traffic Flow Forecasting
MathematicsReliable forecasting of short-term traffic flow is an essential component of modern intelligent transport systems. However, existing methods fail to deal with the non-linear nature of short-term traffic flow, often making the forecasting unreliable ...
Huayuan Chen +5 more
doaj +2 more sources
Short-term intersection traffic flow forecasting [PDF]
, 2020 The intersection is a bottleneck in an urban roadway network. As traffic demand increases, there is a growing congestion problem at urban intersections.
Zhao, Qun +6 more
core +2 more sources
A Graph Deep Learning-Based Fast Traffic Flow Prediction Method in Urban Road Networks
IEEE Access, 2023 In modern smart cities, road networks are becoming more and more complicated, resulting in more complex format of graphs. This brings many challenges to the forecasting of traffic flow in road graphs.
Dongfang Yang, Liping Lv
doaj +1 more source
A intelligent particle swarm optimization for short-term traffic flow forecasting using on-road sensor systems [PDF]
, 2013 On-road sensor systems installed on freeways are used to capture traffic flow data for short-term traffic flow predictors for traffic management, in order to reduce traffic congestion and improve vehicular mobility.
Chan, Kit Yan +3 more
core +1 more source
GSA‐ELM: A hybrid learning model for short‐term traffic flow forecasting
IET Intelligent Transport Systems, 2022 Accurate and timely short‐term traffic flow forecasting is an essential component for intelligent traffic management systems. However, developing an effective and robust forecasting model is challenging due to the inherent randomness and nonlinear ...
Zhihan Cui +5 more
doaj +1 more source
A Two-Stream Graph Convolutional Neural Network for Dynamic Traffic Flow Forecasting
, 2020 Forecasting the traffic flow is a critical issue for researchers and practitioners in the field of transportation. Using the graph convolutional network (GCN) is widespread in traffic flow forecasting. Existing GCN-based methods mostly rely on undirected
Zhaoyang Li +7 more
core +1 more source
Traffic flow forecasting model
Lietuvos Matematikos Rinkinys, 2012 The paper presents a mathematical model based on multicriteria decision making method of the Analytic Hierarchy Process for determining the critical network of railway lines, which prevented the flow of traffic growth, the line bandwidth, traffic volume ...
Beatričė Andziulienė +2 more
doaj +1 more source
Augmented Multi-Component Recurrent Graph Convolutional Network for Traffic Flow Forecasting
ISPRS International Journal of Geo-Information, 2022 Due to the periodic and dynamic changes of traffic flow and the spatial–temporal coupling interaction of complex road networks, traffic flow forecasting is highly challenging and rarely yields satisfactory prediction results.
Chi Zhang +9 more
doaj +1 more source
Tracking Time Evolving Data Streams for Short-Term Traffic Forecasting
Data Science and Engineering, 2017 Data streams have arisen as a relevant topic during the last few years as an efficient method for extracting knowledge from big data. In the robust layered ensemble model (RLEM) proposed in this paper for short-term traffic flow forecasting, incoming ...
Amr Abdullatif +2 more
doaj +1 more source
IEEE Access, 2022 Accurate traffic speed forecasting not only can help traffic management departments make better judgments and improve the efficacy of road monitoring but also can help drivers plan their driving routes and arrive safely and smoothly at their destination.
Yacong Gao +4 more
doaj +1 more source