Langmuir方程参数线性回归与非线性回归的比较
Comparison Between Linear Regression and Nonlinear Regression of Langmuir Equation Parameters
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摘要: Langmuir方程是常用的吸附等温线方程之一，Langmuir方程参数估计有线性回归和非线性回归2种方法。以实测数据为依据，采用IBM SPSS Statistics 24.0软件进行Langmuir方程参数线性回归与非线性回归的对比分析。结果表明：线性回归方法不满足相应曲线因变量的残差平方和最小，线性回归方法中对变量由无理数到有限小数的数值修约是引起舍入误差的原因。基于非线性回归方法对实测数据具有残差平方和较小的特点，在应用Langmuir方程求参数时建议采用非线性回归方法。Abstract: Langmuir equation is one of the commonly used adsorption isotherm equations, there are two methods of Langmuir equation parameters estimation: linear regression method and nonlinear regression method. Based on the measured data, this paper using the IBM SPSS Statistics 24.0 software to compare the linear regression method and nonlinear regression method of Langmuir equation parameters. The results show that the linear regression method does not satisfy the minimum of the residual sum of squares of the dependent variables of Langmuir equation, rounding off for values from the irrational number to finite decimal is the cause of round-off error in the linear regression method. Because the nonlinear regression method has the characteristics of smaller residual sum of squares of the measured data, the nonlinear regression method is recommended in the Langmuir equation.
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