A Refined Mean Field Approximation

Nicolas Gast, B. V. Houdt
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引用次数: 60

Abstract

Stochastic models have been used to assess the performance of computer (and other) systems for many decades. As a direct analysis of large and complex stochastic models is often prohibitive, approximations methods to study their behavior have been devised. One very popular approximation method relies on mean field theory. Its widespread use can be explained by the relative ease involved to define and solve a mean field model in combination with its high accuracy for large systems.
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一个改进的平均场近似
几十年来,随机模型一直被用于评估计算机(和其他)系统的性能。由于对大型和复杂的随机模型的直接分析往往是禁止的,因此设计了近似方法来研究它们的行为。一种非常流行的近似方法依赖于平均场理论。它的广泛应用可以解释为相对容易定义和求解平均场模型,以及它对大型系统的高精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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