Sentence examples for modelling and generating from inspiring English sources

The main contribution of this paper is to significantly advance the uncertainty model of wind power and to provide a systematic procedure for modelling and generating wind power scenarios, which can then be applied to a range of wind power integration problems.

This clearly implies that spread modelling and generating of forecast error bounds are critical as they provide the foundation of decision-making on when trade exits must occur.

Therefore, the entire procedure for modelling and generating wind power forecasting scenarios considering the temporal dependence is described as follows, and the mechanism sketch of each step is drawn in Fig. 2 for further clarification.

From the public health point of view, such information could be useful for human population settlements as well as for monitoring and modelling purposes generating early warning system for implementing interventions.

We present a set of models for simulating vegetation dynamics in disturbance-prone ecosystems with different complexity levels, integrated in a modelling environment for generating landscapes and analysing landscape patterns and simulation results (Lass).

To meet these criteria, a new hybrid modelling approach for generating a simulation model and virtual environment from a process plan is presented.

In this paper, a Pair-Copula modelling approach has been proposed to construct joint distribution and generate scenarios that mimic wind power stochastic behaviours.

To enable a precise, quantitative comparison between different models and to generate the predictions, we simulated all models within the same modelling pipeline.

The scripting/rule-based modelling approach to generating reactions is applicable to other proteins that undergo multiple regulations in a similar manner, for example the insulin receptor substrate IRS-1 [129]–[131] and the C elegans transcription factor SKN-1 (orthologous to NRF TFs in higher organisms) [132].

Hou and coworkers recently introduced mixture modelling to generate a probabilistic E-MAP network to which they applied a Bayesian analysis to identify network modules [ 22], an approach that shows considerable promise.

We compared our model estimates with those recently published by two independent modelling exercises, which generated estimates and projections of T2DM prevalence in a large number of countries around the world, including KSA.