论文标题
适应性复杂性与sndhorn-knopp算法之间的等效性
Equivalence between the Fitness-Complexity and the Sinkhorn-Knopp algorithms
论文作者
论文摘要
我们揭示了在经济复杂性领域开发的健身复杂性算法与sndhorn-knopp算法之间的联系，该算法广泛用于从计算机科学和数学到经济学的不同领域。尽管两种方法之间的形式差异很小，但两者都将同一定点解决方案收敛到归一化。发现的连接使我们能够对适应性和复杂性度量的严格解释作为合适的能量函数的潜力。在这种解释下，高能产品对于低拟合国家来说是不可行的，这解释了为什么该算法有效地在两部分网络中显示嵌套模式。我们还表明，提出的解释揭示了健身复合算法的规模不变性，该算法对算法在不同数据集中的实现具有实际影响。此外，对新观点的经验贸易数据的分析揭示了三类可能从不同发展策略中受益的国家。
We uncover the connection between the Fitness-Complexity algorithm, developed in the economic complexity field, and the Sinkhorn-Knopp algorithm, widely used in diverse domains ranging from computer science and mathematics to economics. Despite minor formal differences between the two methods, both converge to the same fixed-point solution up to normalization. The discovered connection allows us to derive a rigorous interpretation of the Fitness and the Complexity metrics as the potentials of a suitable energy function. Under this interpretation, high-energy products are unfeasible for low-fitness countries, which explains why the algorithm is effective at displaying nested patterns in bipartite networks. We also show that the proposed interpretation reveals the scale invariance of the Fitness-Complexity algorithm, which has practical implications for the algorithm's implementation in different datasets. Further, analysis of empirical trade data under the new perspective reveals three categories of countries that might benefit from different development strategies.
