中文标题#
從一些著名擁堵交通網絡的用戶行為中學習
英文标题#
Learning from user's behaviour of some well-known congested traffic networks
中文摘要#
我們考慮在均衡條件下預測擁擠交通網絡中用戶行為的問題，即交通分配問題。 我們提出了一種兩階段的機器學習方法，該方法將神經網絡與固定點算法相結合，並在幾個經典的擁擠交通網絡上評估了其性能。
英文摘要#
We consider the problem of predicting users' behavior of a congested traffic network under an equilibrium condition, the traffic assignment problem. We propose a two-stage machine learning approach which couples a neural network with a fixed point algorithm, and we evaluate its performance along several classical congested traffic networks.
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