Piccoli, Traffic Flow on Road Networks, SIAM Journal on Mathematical Analysis, 36:1862- 1886, 2005.G. M. Coclite, M. Garavello, and B. Piccoli, Traffic flows on road networks. SIAM J. Math. Anal. 36 (2005), 1862–1886. MATH MathSciNet...
ANALYSIS OF TRAFFIC FLOW ON COMPLEX NETWORKS. We propose a new routing strategy for controlling packet routing on complex networks. The delivery capability of each node is adopted as a piece of local i... LI,KUN,GONG,... - 《International Journal of Modern Physics B Condensed Matter Physics...
traffic flow名— 车流量名 traffic名— 交通名 · 车流名 · 车辆名 · 车行名 · 贩卖名 flow动— 流动 · 流向动 · 流动动 · 流通动 · 传播动 · 流淌动 · 洋溢动 · (话语)流利动 · 充满动 flow名— 流量名 · 流动名 network名— ...
Neural Network ensemble is firstly applied to forecast traffic flow,which can improve remarkably the generalization ability of learning systems through training several neural networks and then combining their results.Based on Boosting and Bagging,the method of neural network ensemble with the strategy of...
Road Network Traffic Flow Prediction Method Based on Graph Attention Networks With the acceleration of urbanization and the continuous growth of transportation demand, the traffic management of smart city road networks has become inc... J Wang,S Yang,Y Gao,... - 《Journal of Circuits Systems &...
flow forecasting is crucial for making appropriate route guidance and vehicle scheduling schemes in intelligent transportation systems. However, recent gra... XiaZhichao,ZhangYong,YangJielong,... 被引量: 0发表: 2024年 Traffic Prediction Based on Dynamic Temporal Graph Convolutional Networks Traffic predi...
Considering the periodic characteristics of traffic flow, this paper trains the model according to the traffic flow data of three different cycles: adjacency, daily, and weekly cycle time. Each space–time block is composed of two graph attention networks and a gated recurrent unit, which are ...
基于时空多任务学习框架(MDL)的区域交通流量预测与流向预测(Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning) 2019TKDE 设计了一个深度神经网络来预测顶点流量(命名为 NODENET),另一个深度神经网络预测边流量(命名为 EDGENET)。通过将他们的隐藏状态拼接来连接这两个深度神经网络,并一同...
Freeway.By taking advantage of structures of neural network being determined by embedding dimension of phase space reconstruct,neural network model of traffic flow for freeway based on chaos theory is put forward.Practical data show that the method is able to do short-term traffic flow prediction...
Flow-based data sets are necessary for evaluating network-based intrusion detection systems (NIDS). In this work, we propose a novel methodology for generating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image ...