MFF中采用了有特色的概率相关系数对GEP中的适应度函数进行优化，使得精度提高了27%。
MFF optimizes the fitness function in GEP by special approach called probability correlation factor, which increases the precision by 27%.
应力-应变等时曲线线性回归函数的相关系数均高于0。
The correlative coefficients of linear regression function for isochronous stress-strain curve are all higher than 0.
不同林分的抗蚀指数与时间的动态模拟关系为二次幂函数曲线，相关系数0.9以上。
The analog equation between soil erosion resistance index and time is quadratic power function curve, whose correlation coefficient is above 0.9.
以测定结果的响应信号作为被测物浓度的函数作图，相关系数应大于0.99。
Calculate the regression line of test results versus analyte concentrations. The correlation coefficient should be more than 0.99.
结果双变量多水平模型可以估计各水平两个变量的方差协方差阵，据此可以计算出相关系数随协变量变化的函数式。
Results Multilevel models can present the variance covariance metrics of two dependent variables in every levels, and make out the functional expresses of correlation coefficient with covariates.
同时，通过引入相应的映射关系，将拟合谱与待分析谱之间的相关系数和目标函数同时映射到了遗传算法的适值函数域中，获得了较高的分析精度。
At the same time, it can get more precise values by putting related coefficient of fitting spectrum and objective function into Genie Algorithm fitness function.
同时，通过引入相应的映射关系，将拟合谱与待分析谱之间的相关系数和目标函数同时映射到了遗传算法的适值函数域中，获得了较高的分析精度。
At the same time, it can get more precise values by putting related coefficient of fitting spectrum and objective function into Genie Algorithm fitness function.
应用推荐