The RBF network function approximation theory and method are introduced, and the method of nonlinear error correction of sensor is presented based on generalized regression neural network(GRNN).
介绍了径向基函数网络的函数逼近原理和方法，提出了一种基于广义回归神经网络（GRNN）的传感器非线性误差校正方法。
Optimization means include improvement of prediction strategy, theoretical formula calculation instead of empiric constants, and correction of formula factors with actual data 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。
An error correction method for three axial fluxgate sensor based on support vector regression (SVR) is proposed.
提出了一种基于支持向量回归机(SVR)的三轴磁通门传感器误差修正方法。
The result of variance analysis revealed that regression equation method could give a more reliable result than leaf area correction coefficient method for the leaf area measurement.
经方差分析比较证明，应用回归方程法计算的叶面积比用矫正系数法更为可靠。
Descusses the logarithmic correction factors of general multiplicative regression model and percent bias of unadjusted predicted value. The pool of correction factors is proposed.
文中讨论了一般乘法回归模型的对数改正系数和未校正预测值的相对偏差，提出了对数改正系数的合并问题。
Descusses the logarithmic correction factors of general multiplicative regression model and percent bias of unadjusted predicted value. The pool of correction factors is proposed.
文中讨论了一般乘法回归模型的对数改正系数和未校正预测值的相对偏差，提出了对数改正系数的合并问题。
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