Sentence examples for models using sequential from inspiring English sources
In this study, a feature-based simplification method of boundary representation (B-rep) models using sequential iterative volume decomposition is proposed.
Variograms were then built to capture the spatial variation in permeability between data points which was then used in the building of equiprobable realizations of the permeability distribution across the model using sequential Gaussian simulation (SGSIM).
Decay of Pt was modelled using sequential measurements of Pt levels in serum and urine combined with the administered dose of cisplatin, age, weight and height at the start of chemotherapy.
Two models were developed using sequential multiple regression to determine prediction of, social and emotional loneliness from those IVs having significant bivariate association with either DVs.
A multivariable logistic regression main-effects model was developed, using sequential backward elimination of non-significant variables (based on the model deviance statistic).
The hyperparameters in the probabilistic model are learned using sequential Monte Carlo (SMC) method, which is superior to standard Markov chain Monte Carlo (MCMC) methods for multi-modal distributions.
The source model was constructed using sequential strategy regarding global field power and residual variance [61], [62].
The most relevant features for each model were chosen using sequential forward floating selection (SFFS).
Combining results from Monte Carlo simulations, we analyze quantitatively the mixed spectra of the models using a sequential quadratic programming method and compare the results to those obtained with the weighted least-squares method.
Heritability and genetic correlations were estimated by variance component models using SOLAR (Sequential Oligogenic Linkage Analysis Routines, version 4.1.5), a computer package designed for variance component and linkage analysis in pedigrees of arbitrary size and complexity (Almasy & Blangero 1998).
We calculated PAFs directly from our multivariable logistic regression models using the sequential and average attributable fraction method which takes into account that ORs are adjusted for confounders [ 22].
