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A universal model for mobility and migration patterns

机译:迁移和迁移模式的通用模型

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摘要

Introduced in its contemporary form in 1946 (ref. 1), but with roots that go back to the eighteenth century, the gravity law is the prevailing framework with which to predict population movement, cargo shipping volume and inter-city phone calls, as well as bilateral trade flows between nations. Despite its widespread use, it relies on adjustable parameters that vary from region to region and suffers from known analytic inconsistencies. Here we introduce a stochastic process capturing local mobility decisions that helps us analytically derive commuting and mobility fluxes that require as input only information on the population distribution. The resulting radiation model predicts mobility patterns in good agreement with mobility and transport patterns observed in a wide range of phenomena, from long-term migration patterns to communication volume between different regions. Given its parameter-free nature, the model can be applied in areas where we lack previous mobility measurements, significantly improving the predictive accuracy of most of the phenomena affected by mobility and transport processes.
机译:引力定律于1946年以当代形式推出(参考资料1),但其起源可以追溯到18世纪,是预测人口流动,货物运输量和城市间电话呼叫的主要框架。国家之间的双边贸易流动。尽管已被广泛使用,但它依赖于可调参数,该可调参数因地区而异,并且存在已知的分析不一致的问题。在这里,我们介绍一个捕获本地流动性决策的随机过程,该过程有助于我们分析性地得出通勤和流动通量,这些通量和流动通量仅需要人口分布信息。从长期迁移模式到不同区域之间的通信量,最终的辐射模型预测的迁移率模式与在广泛现象中观察到的迁移率和传输模式非常吻合。鉴于其无参数的性质,该模型可用于我们缺乏先前流动性测量的区域,从而大大提高了受流动性和运输过程影响的大多数现象的预测准确性。

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  • 来源
    《Nature》 |2012年第7392期|p.96-100|共5页
  • 作者单位

    Center for Complex Network Research and Department of Physics, Biology and Computer Science, Northeastern University, Boston, Massachusetts 02115, USA,Dipartimento di Fisica 'G. Galilei',Universita di Padova, CNISM and INFN, via Marzolo 8, 35131 Padova, Italy,Institute of Physics, Budapest University of Technology and Economics, Budafoki ut 8, Budapest. H-1111, Hungary;

    MIT,Department of Civil and Environmental Engineering, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA;

    Dipartimento di Fisica 'G. Galilei',Universita di Padova, CNISM and INFN, via Marzolo 8, 35131 Padova, Italy;

    Center for Complex Network Research and Department of Physics, Biology and Computer Science, Northeastern University, Boston, Massachusetts 02115, USA,Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston,Massachusetts 02115, USA,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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  • 正文语种 eng
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