Sentence examples for model that optimally from inspiring English sources

Therefore, in order to overcome existing analytic weaknesses, we propose a model that optimally subdivides a predetermined rail transit line into sections for phased development and optimizes the implementation times of those sections over a planning horizon.

Exploratory SEM established the interregional covariances of activity to define their directionality and strength for connectivity models generated from the four regions of interest (ROI) (FP, PCC, pSTS, and rACC) comprising the constrained anatomical model that optimally fit data from each of the three conditions (neutral, care, and justice).

The model that optimally explained the data consisted of a single effect for the step factor, b = -0.941, p <.001.

The aim of this study was to identify a MetS model that optimally predicts type 2 diabetes and CVD while still representing a single entity.

Once a MetS model that optimally predicts type 2 diabetes and CVD, while still representing one disorder, has been identified, future research could focus on the pathophysiology behind this single MetS entity.

The goal of feature selection is to identify such a panel of genetic and other risk factors, which result in a model that optimally predicts the phenotypic response variables, either the class labels in case-control classification (e.g. disease vs. healthy), or quantitative phenotypes in regression problems (e.g. height prediction).

We then compared combinations of bilinear and nonlinear dynamic causal models (Friston et al. 2003) to identify connectivity models that optimally explain how interactions between these form and motion pathways could generate STS responses to dynamic faces.

The goal of this prospective, population-based study is to develop statistical models that optimally predict chronic work disability from data obtained from administrative databases and worker interviews soon after a work injury.

The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view.

Faced with this dichotomy, we propose a Mixed Integer Programming (MIP) model that can optimally schedule fuel treatments to reduce fuel hazards by fragmenting high fuel load regions while considering critical ecological requirements over time and space.

Unfortunately, as a low signal-to-noise ratio is a frequent problem in sequence analysis, such studies require careful selection of a background model that will optimally reduce this biological 'noise' [ 11, 15].