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Report Summarizes Advanced Transportation Study Findings from Beijing Key Laboratory (Spatiotemporal DeepWalk Gated Recurrent Neural Network: A Deep Learning Framework for Traffic Learning and Forecasting)

机译:报告总结了北京关键实验室的高级运输研究结果(时空深行门控复发神经网络:交通学习和预测的深度学习框架)

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摘要

By a News Reporter-Staff News Editor at Network Daily News – Researchers detail new data in advanced transportation. According to news reporting originating from the Beijing Key Laboratory by NewsRx correspondents, research stated, “As a typical spatiotemporal problem, there are three main challenges in traffic forecasting.” Funders for this research include National Natural Science Foundation of China.
机译:由Network Daily News的News Reporter-Staft新闻编辑 - 研究人员详细介绍了高级运输中的新数据。 根据NewsRX通讯员源自北京关键实验室的新闻报道,研究指出:“作为典型的时空问题,交通预测有三个主要挑战。” 这项研究的资助者包括中国国家自然科学基金会。

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