Sentence examples for modelling approaches that from inspiring English sources

Our results confirm that robust models can be generated with logistic regression using randomly selected pseudo-absences, and that such models outperform profile techniques and two-step modelling approaches that use intermediate models to select pseudo-absences.

We found that the modelling approaches that account for model uncertainty out-performed the stepwise strategy when used to predict MRSA carriage risk.

Any solutions designed using modelling approaches that do not consider uncertainty associated with model input and model parameters may be significantly over-dimensioned or under-dimensioned.

To this extent, the specific scope of this paper is to present a comprehensive identification procedure for evaluating load models under different loading conditions and further to propose two generic modelling approaches that can be used to derive robust load models that are suitable for dynamic simulations over a wide range.

Next, the characteristics of the six modelling approaches that were distinguished are described: distance-dependent stand models, distribution models, average tree models, distance-dependent tree models, distance-independent tree models and gap models.

The literature identifies a number of fundamental features of modelling approaches that can be used to characterise public health modelling problems [12 14].

The Network-Oriented Modelling approach based on adaptive temporal causal networks, as described here (see also [1, 10]), provides a dynamic modelling approach that enables a modeller to design high-level conceptual model representations in the form of cyclic graphs (or connection matrices).

By the example of a fish-plankton lake ecosystem we demonstrated that a well-designed switching hybrid model can be a performant modelling approach that retains relevant spatial and attributive information.

Within the fundamentals of the proposed phenomenological modelling approach that guide the model structuring, the process tasks are decomposed into the relevant phases and physicochemical phenomena involved, identifying the connections and influences amongst them and evaluating the individual rates.

This study explores agro-ecosystem modelling using an interaction graph-based modelling approach that explicitly link elements at different scales without up or downscaling.

Spatial Simulation is a spatially explicit, bottom-up modelling approach that includes individual-based models and cellular automata.