应用萤火虫算法拟合bsamzier曲线Van der Waals状态方程

Almudena Campuzano, A. Iglesias, A. Gálvez
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引用次数: 3

摘要

范德华方程是一个推广理想气体定律的状态方程。它包括两条特征曲线,称为双节曲线和单节曲线。它们通常通过标准多项式拟合来重建。然而,得到的拟合模型在几个方面有很大的局限性。在本文中,我们通过使用自由形式的贝塞尔曲线对二维点集进行最小二乘逼近来解决这个问题。这除了计算曲线的极点外,还需要执行数据参数化。这是通过应用一种强大的群体智能方法——萤火虫算法来实现的。该方法已应用于某气体的实测数据。结果表明,该方法能较好地重建特征曲线。比较工作表明,我们的方法在本例中优于两种最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying Firefly Algorithm to Data Fitting for the Van der Waals Equation of State with Bézier Curves
The Van der Waals equation is an equation of state that generalizes the ideal gas law. It involves two characteristic curves, called binodal and spinodal curves. They are usually reconstructed through standard polynomial fitting. However, the resulting fitting models are strongly limited in several ways. In this paper, we address this issue through least-squares approximation of the set of 2D points by using free-form Bezier curves. This requires to perform data parameterization in addition to computing the poles of the curves. This is achieved by applying a powerful swarm intelligence method called the firefly algorithm. Our method is applied to real data of a gas. Our results show that the method can reconstruct the characteristic curves with good accuracy. Comparative work shows that our approach outperforms two state-of-the-art methods for this example.
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