Sentence examples for predictor parameters and from inspiring English sources
Non-linear power function techniques were used to develop allometric models from predictor parameters and their interactions to predict individual woody plant branch and stem biomass and total AGB separately for the selected two woody species.
Interestingly, spike duration was found to be the most reliable predictor parameter, and its measurement at each time-point tested.
Due to the increased genomic coverage and robust expression measurements the HuEx-1.0ST mapping were used to calculate the predictors' parameters and validate the model.
The process of building a robust gene expression predictor has two main steps: 1) unbiased selection of the predictor model parameters and 2) estimation of the predictor model generalisability [19].
Seven predictor parameters have been used in regression analysis and ANN to predict trip time.
Results: Multivariate logistic regression analysis revealed that the only independent predictor parameters were thick papillary projections, solid areas, central flow, and velocimetric features of high velocity and low resistance.
The main FA detection model is based on Bayesian theorem at which four predictor parameters including PERSIANN rainfall estimations, brightness temperature (Tb), precipitable water (PW) and near surface air temperature (Tair) is considered as its input dataset.
One of the models is based on the chain saw penetration index, and uses the uniaxial compressive strength of the stone, weight of the chain saw machine and useful cutting depth of the arm as predictor parameters.
(b) The correlation matrix of parameters is the minor product moment of the standardized predictor measures divided by N and is given by R = left( {x^{prime} times x} right)/N (2) where, x′ denotes the transpose of the standardized matrix of predictor parameters 2.
The other model is based on the results of linear cutting experiments performed in the unrelieved cutting mode with a standard chisel tool and uses specific energy as the predictor parameter.
Seismic response and vulnerability assessment of key infrastructure elements, such as highway bridges, often requires a large number of nonlinear dynamic analyses of complex finite element models to cover the predictor parameter space.
