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1)  stepwise regression arithmetic
逐步回归算法
1.
This article analyses the source of temperature error of vibrational canister barograph and discusses the application of stepwise regression arithmetic used in the temperature compensation and calibration of vibrational canister barograph.
介绍了振筒气压仪温度误差的来源 ,讨论了逐步回归算法在振筒气压仪温度补偿和校准中的应用 ,并以一只振筒的校准算法为例 ,给出了校准方程 ,分析了结果 ,阐述了此项工作对提高和保持振筒气压仪测量精度的意义。
2)  stepwise regression
逐步回归法
1.
Since variable selection is important in quantitative structure property/activity studies, in this paper comparison between the genetic algorithm and several common methods such as forward method, backward elimination and stepwise regression is performed.
鉴于变量选择在 QSAR/QSPR研究中的重要性 ,比较了遗传算法和几种传统的方法 ,如前进法、后退法及逐步回归法 。
2.
First the stepwise regression was applied to screen the habitat factors,then analytic hierarchy(AHP) process was applied to determined the weights of the factors.
首先应用逐步回归法筛选出了4个影响显著的生境因子坡向、坡度、海拔和土层厚度;通过层次分析法确定了各显著影响因子的权重,海拔的权重为0。
3)  the method of stepwise regression
逐步回归法
1.
The temperature compensating model is gained in the help of the method of stepwise regression by temperature experiment repeated, and its applicability is validated.
通过重复性温度实验,利用逐步回归法得到了温度补偿模型,并对模型的实用性进行了实验验证。
2.
The relation of RLG s bias and temperature was analyzed in the help of the method of stepwise regression by temperature experiment repeated.
通过重复性温度实验,利用逐步回归法分析了机抖激光陀螺零偏与温度的关系,得到了零偏的实时温度补偿模型。
3.
The new kind of temperature compensating model is established in the help of the method of stepwise regression by lots of high-low temperature experiment repeated.
通过大量高低温环境的重复性温度实验,利用逐步回归法建立了一种零偏温度补偿模型,并对该模型的补偿效果进行了实验测试。
4)  Stepwise regression method
逐步回归法
1.
Establishment of TA15 titanium alloy constitutive model based on stepwise regression method;
基于逐步回归法的TA15钛合金本构模型的建立
2.
Application of stepwise regression method in flood level forecast of the lower Yellow River;
逐步回归法在黄河下游洪水水位预测中的应用
3.
The“optimum”independent variable subsets of macro-variables testable(deformation temperature、strain rate and strain)influencing the flow stress have been determined by using stepwise regression method.
利用逐步回归法确定了影响流动应力的宏观可测变量(变形温度、应变速率和应变)的“最优”自变量子集,基于热压缩实验数据和部分神经网络预测数据,利用最小二乘估计算法求解模型回归参数值,建立了基于逐步回归法的 TAl5的材料本构模型。
5)  principal component-stepwise regression algorithm
主成分-逐步回归算法
6)  stepwise regression method
逐步回归方法
1.
Based on the capacitance distributions from 12-electrod capacitance sensor,using stepwise regression method,the capacitance relation of oil-gas two phase flow based on flow pattern is developed.
基于12电极阵列电容传感器提供的电容测量信息,采用逐步回归方法,获得了与流型相关的电容关联式。
2.
Based on D-S evidence theory and stepwise regression method,combining the power spectrum density function characteristics of differential pressure fluctuation signals and capacitance information from capacitance sensor,a new flow pattern identification method of oil-gas two phase flow was proposed.
基于D-S证据理论和逐步回归方法,结合直管段差压波动信号的功率谱密度分布特征和电容传感器提供的电容信息,给出了一种油气两相流流型辨识的数据融合方法。
补充资料:逐步回归
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性质:在建立多元回归方程的过程中,按偏相关系数的大小次序将自变量逐个引入方程,对引入方程中的每个自变量偏相关系数进行统计检验,效应显著的自变量留在回归方程内,循此继续遴选下一个自变量。如果效应不显著,停止引入新自变量。由于新自变量的引入,原已引入方程中的自变量由于变量之间的相互作用其效应有可能变得不显著者,经统计检验确证后要随时从方程中剔除,只保留效应显著的自变量。直至不再引入和剔除自变量为止,从而得到最优的回归方程。

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