Sentence examples for forecasting and identify from inspiring English sources
In order to describe the importance of uncertainty analysis in seawater intrusion forecasting and identify the main factors that might cause great differences in prediction results, we analyzed the influence of sea level rise, tidal effect, the seasonal variance of influx, and the annual variance of the pumping rate, as well as combinations of different parameters.
Programs written for Google's soon to be released Android mobile platform, for instance, will be able to tap a user's location to automatically update weather forecasts and identify the lowest price for a particular book in his neighborhood features not currently available on U.S. cellphones.
Without standards for sustainability information, investors are limited in their ability to forecast challenges and identify opportunities.
With no sustainability standards set in place, investors are limited in their ability to forecast challenges and identify opportunities.
Since facilities in some of the surveyed countries rely on off-grid energy sources, better assessment by energy source and by combinations of sources is critical to forecasting needs and identifying optimal energy solutions in diverse settings.
Reference [10] used the discrete Hilbert transform as minimum phase type filter to forecast wind speed and identify the characterization of wind speed.
In 2002 the World Health Organization identified high blood pressure as the leading risk factor for death, forecasting an epidemic of hypertension and identifying community programmes to prevent cardiovascular disease as a priority.
The current study proposes a new object-based method, named PERCAST (PERsiann-ForeCAST), to identify, track, and nowcast storms.
This challenge cannot be met by traditional methods, and a new method to combine forecasts should identify what additional information a model can contribute to an existing forecast.
We predicted the habitat distributions for 27 bird species of Anseriformes in Iran using an ensemble forecasting framework to identify biodiversity hotspots.
One of the most challenging problems in technological forecasting is to identify as early as possible those technologies that have the potential to lead to radical changes in our society.
