基于支持向量机的弗兰克-赫兹实验曲线拟合

Curve Fitting of Frank Hertz Experiment Based on Support Vector Machine

弗兰克-赫兹实验是“近代物理实验”中的重要实验之一,数据量大且数据处理复杂。支持向量机是一种广泛应用于函数逼近、模式识别、回归等领域的机器学习算法。本文将支持向量机算法应用于弗兰克-赫兹实验数据的拟合,过程简单,在python环境下验证该方法拟合精度高,效果好。支持向量机算法还可应用于其他的物理实验曲线拟合。

Frank-Hertz experiment is a classical experiment in modern physics experiments.It has a large amount of experimental data and a complicated data processing process.Support Vector Machine is a machine learning algorithm which widely used in function approximation,pattern recognition,regression and other fields.In this paper,support vector machine is used to do curve fitting for the experimental data of Frank-Hertz experiment.The process is simple,and the method is verified to have high curve fitting accuracy and good effect in python environment.SVM can also be applied to curve fitting in other physics experiments.