Sentence examples for forecasts arose from inspiring English sources

Later in the day, several different track forecasts arose.

Some interesting lag effects, which are of value in long-range weather forecasting, arise through the considerably slower circulation of the ocean.

The benefits of long-term water demand forecasting arise from the avoidance of under- or over investment.

Another reason for not using environmental forecasts which arose in discussions with both hydrological and ocean rig stakeholders was the multifaceted nature of decisions.

The Congressional Budget Office's consistent forecasting errors arose not from any partisan bias, but from its methods of projection.

The total number of injected counts over the duration of each outbreak also varied randomly (uniformly) from 5 to 50 times the standard deviation of the forecast errors arising from using forecast method 1 (see below) in the training data for all eight years.

Using real respiratory syndrome counts collected from the BSafer system [ 6] from 2/1/94 5/31/03, we varied the length of training data from one to eight years, applied a sequential test to the forecast errors arising from each of eight forecasting methods, and evaluated the DP on the basis of injected synthetic outbreaks and the use of Page's test to detect anomalous values.

Using real respiratory syndrome counts collected in an emergency department from 2/1/94 5/31/03, we varied the length of training data from one to eight years, applied a sequential test to the forecast errors arising from each of eight forecasting methods, and evaluated their detection probabilities (DP) on the basis of 1000 injected synthetic outbreaks.

In contrast, forecast errors arising from using Eq. (1) to forecast data simulated from Eq. (1) (the nonhierarchical model) tend to have unrealistically ideal behaviour with negligible serial correlation.

As a consequence, forecast errors arising from using Eq. (1) to forecast real data reflect modeling imperfections (leading for example to serial correlation in the errors) as well as purely random variability.

It is also applicable to capacity investment and inventory/production management problems with demand/supply forecast updates arising in operations and hydropower-reservoir management.