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The present study aims at evaluating the error in the laminar burning speed evaluation induced by using the traditional linear methodology.
The framework is a linear methodology which is based upon obtaining in turn output from each of the following analyses: hazard analysis; structural analysis; loss analysis, and finally decision making based on variables of interest, such as downtime or cost to repair.
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Data were analyzed within-year (generation) using linear model methodology.
The aim of the penalised linear regression methodology was to determine those miRNA which most strongly predict (positively or negatively), the gene expression summary score for each signature.
A simplified linear static methodology, applicable to buildings with flexible diaphragms, is proposed in this paper.
This novel element is formulated using the method of partial wave techniques (PWT) in conjunction with linear algebraic methodology.
A linear assessment methodology was developed for the conformational data in the Pura Raza Español horse (Andalusian horse).
In particular, the linear regression methodology and the radial basis function (RBF) neural network architecture are utilized for producing the input output "meta-models".
Moreover, in order to verify the linear analysis methodology, a numerical strategy is adopted to solve the nonlinear governing equations and to investigate the natural circulation dynamics in the time domain.
The linear surface methodology was used to map the simulation output, which is the loss in gas production (GPL), compared to the clean case (i.e., 100% clean-up) after three production periods of 10, 30 and 365 days.
Previous studies on modeling the relationships between influential features and the energy consumption have several gaps and limitations, such as the linear modeling methodology and insufficient consideration of particular features.
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