本文讨论回归系数相同，回归常数不同的回归分析模型。
This paper presents regression model with same regression coefficient and different regression constants.
以标准封头的容积回归，得出不同形状封头的回归常数。
Based on the volume regression of the typical heads, the regression coefficients of the heads with different shapes are obtained.
为了加快符号回归常数模算法(SRCMA)的收敛速度，本文提出了一种适合于BPS K信号的快速算法。
For increasing the speed of convergence of the signed regressor constant modulus algorithm (SRCMA), a fast SRCMA algorithm suitable for real BPSK signals is presented.
第二类模式是一种速率的经验式，其中速率常数及反应顺序取决于对实验结果的线性回归的讨论。
The second type of these models is an empirical rate expression, which rate constants and reaction orders are determined by dealing the experimental results with linear regression.
线性回归得出化学反应速率常数表观值。
The apparent reaction rate constant can be obtained by linear regression.
其中优化手段主要包括预测策略的改进，采用理论公式计算值替代经验常数，通过实际数据回归修正公式系数等。
Optimization means include improvement of prediction strategy, theoretical formula calculation instead of empiric constants, and correction of formula factors with actual data regression.
利用线性回归建模时，一般都采用有常数项的模型，而不去考虑它对回归的作用是否显著。
There is a regression constant in the linear regression model. But it is not significant in some conditions.
本文从恒压过滤速率方程出发，利用多项式回归的方法求取过滤常数，并以一实例将之与教材中介绍的方法进行了比较。
The polynomial regression based on the constant-pressure filtration rate equation has been presented to handle the experimental data and compared with the methods in literature through an example.
运用MC模拟试验，建立了平均晶粒尺寸与蒙特卡罗步数之间的关系，利用回归分析方法确定了MC模型常数。
Through MC simulation test, the relation of average grain size and Monte Carlo steps was established and the parameters of MC model were work out by the method of regression analysis.
根据多元酸碱滴定计算通式，针对实际情况化简后，非线性回归同时求出浓度和条件离解常数。
On the basis of our mathematic models of the titration, the content and conditional dissociation constant may be determined by using nonlinear regression.
由于常规线性回归模型对个别异常数据敏感，导致回归方程欠稳定。
On account of the conventional linear regression model is sensitive to specific abnormal data, thus leads to instability of the regression equation.
该模型通过隶属度加权来削弱个别异常数据对回归直线的影响，从而达到提高回归方程稳定性的目的。
By means of weighted subordination degree this model weakens the influence of distinct abnormal data affecting upon the regression straight line and...
该模型通过隶属度加权来削弱个别异常数据对回归直线的影响，从而达到提高回归方程稳定性的目的。
By means of weighted subordination degree this model weakens the influence of distinct abnormal data affecting upon the regression straight line and...
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