Sentence examples for the development of predictions from inspiring English sources

This can be built onto existing risk assessment tools such as CLEA through the development of predictions of the consequences of modelled pollutant exposures to health, together with parallel assessment of health benefits.

The development of predictions of the measurements during a simulation run with the final estimated parameters is shown in Figures 10 and 11 for the run with the standard particle filter, and in Figures 12 and 13 for the run with the MTU particle filter.

It is encouraging and worth noting, that in silico modelling has shown some promise as another potential tool in understanding the underlying mechanisms of tumour biology and the development of predictions of tumour response to different drugs (such as cisplatin and doxorubicin).

Evaluation of the ability of a survival model to predict future data is the most important consideration in the development of prediction model.

Such a large meteorological data set for the location under observation is usually unavailable, so upcoming work includes the development of prediction algorithms capable of handling small data sets.

Thus, we discuss in this section related work that investigates influencing factors on issue fix time or vulnerability fix time and also the development of prediction models for effort estimations, and differentiates them from our work.

These findings indicate that the relationships between multiple climatic factors and bacterial FBD incidence can be valuable for the development of prediction models for future patterns of diseases in response to changes in climate.

The development of prediction methods is needed because even current high-throughput techniques, such as SPOT, are limited to rather small sequence variations [16].

However, information regarding negative training/test datasets (definitely determined non-functional sites) is scarce, which is a choke point for the development of prediction models.

The major goal of this study will be the development of prediction rules and diagnostic algorithms for individual patients.

The development of prediction models then becomes a problem of binary classification, even though often multiple differential diagnoses exist.