Sentence examples for of multiple determinations from inspiring English sources
The statistical coefficient of multiple determinations (R2 value) equals to 1, 0.9996, 1 for the COP, ECOP and F, respectively.
(HHV)I = Measured high heat value of the fuel, for sample period "i" (which may be the arithmetic average of multiple determinations), or, if applicable, an appropriate substitute data value (mmBtu per mass or volume).
The statistical coefficient of multiple determinations (R2 – value) equals to 0.976, 0.9825, 0.9855 for the coefficient of performance (COP), exergetic coefficient of performance (ECOP) and circulation ratio (F), respectively.
The best statistical coefficients of multiple determinations (R2-values) equal 0.99995, 0.99997 and 0.99995 for the coefficient of performance (COP), exergetic coefficient of performance (ECOP) and circulation ratio (F), respectively obtained by the LM algorithm with seven neurons.
The lack-of-fit test results and the high value of coefficients of multiple determinations showed the adequacy of this analytical method to predict the required performance of eco-efficient UHPC.
The best statistical coefficient of multiple determinations (R2-value) for training data equals to 0.999715, 0.995627, 0.999497, and 0.997648 obtained by different algorithms with seven neurons for the non-dimensional exergy losses of evaporator, generator, absorber and condenser, respectively.
A series of models were constructed using these covariates, with the optimal model determined by the adjusted coefficient of multiple determination Ra (adjusted R-square) criterion.
Value of coefficient of multiple determination are achieved.
The standardized regression coefficients, the Pearson correlation coefficients as well as the coefficient of multiple determination R2 are discussed.
According to analysis of variance (ANOVA) the coefficient of multiple determination of 0.841 was obtained for RSM and 0.974 for ANN.
The performance of the NN analysis was evaluated using a statistical indicator (the coefficient of multiple determination), and by examination of the error patterns.
