Center for Complex Network Research and Department of Physics, Biology and Computer Science, Northeastern University, Boston, Massachusetts 02115, USA.
Nature. 2012 Feb 26;484(7392):96-100. doi: 10.1038/nature10856.
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.
自 1946 年(参考文献 1)以现代形式引入以来,重力定律一直是预测人口流动、货物运输量和城市间电话通话量以及国家间双边贸易流量的主要框架。尽管它被广泛使用,但它依赖于可调参数,这些参数因地区而异,并且存在已知的分析不一致性。在这里,我们引入了一种捕捉局部流动性决策的随机过程,可以帮助我们分析得出通勤和流动性通量,而这些通量仅需要关于人口分布的信息作为输入。所得到的辐射模型预测的流动模式与从长期迁移模式到不同地区之间的通信量等广泛现象中观察到的流动和交通模式非常吻合。由于其无参数的性质,该模型可以应用于我们缺乏先前流动测量的领域,显著提高了受流动和交通过程影响的大多数现象的预测准确性。