CAJ | 학술논문

在工程应用和科学实验中，曲线拟合是对系统做出结论或预测的重要手段。因此拟合误差变得非常重要，而最小二乘法作为曲线拟合最常用的方法，因其更为准确、实用而被广泛应用。该文就最小二乘法对实验所获得的数据进行曲线拟合，并对整个拟合过程进行归纳和总结，其中一些主要步骤是在Matlab中实现的。
재공정응용화과학실험중，곡선의합시대계통주출결론혹예측적중요수단。인차의합오차변득비상중요，이최소이승법작위곡선의합최상용적방법，인기경위준학、실용이피엄범응용。해문취최소이승법대실험소획득적수거진행곡선의합，병대정개의합과정진행귀납화총결，기중일사주요보취시재Matlab중실현적。
In engineering applications and scientific experiments, curving fitting is an important method to make a summary or prediction for a system. Therefore, the error of curving fitting becomes extremely im- portant. The most popular method in curving fitting is least square method, which is widely used because it is more accurate and practical. The article curve-fits the data of experiment by way of least square meth od, and concludes and summarizes the whole process of curving fitting, in which some main procedures are processed in matlab.