Sentence examples for lead to forecast from inspiring English sources

Exact(1)

In order for simulated data to lead to forecast errors that better represent those resulting from real data we introduce a hierarchical model.

Similar(59)

The fact that estimates of the current state are inaccurate and that numerical models have inadequacies, leads to forecast errors that grow with increasing forecast lead time.

And those hours are being used up already, as the high price of natural gas makes burning cheaper coal attractive now.This looming double whammy has led to forecasts of shortages as the amount of spare capacity in the system drops.

Worse, as signs of weakness accumulate, forecasters have trimmed estimates for the current quarter from around 3.5% they were projecting a month ago to 2.7% or less now.Last December an agreement between Barack Obama and the Republicans to extend George Bush's tax cuts and enact new ones led to forecasts of 3% to 4% growth this year.

Mixed messages in economic data and corporate reports, combined with heightened uncertainty about the midterm elections, have led to forecasts of both soaring and plunging stock prices, resurgent inflation and insidious deflation, and slow but steady economic growth and a double-dip recession.

Sheats [9] notes how the prevalent notion that organic electronic technology equals low-cost production led to forecasts about economic potential in a variety of markets.6 The numbers read like a forecasting race: who can top the previous high forecast?

They observe that higher levels of forward-looking disclosures lead to increased forecast accuracy.

In other two methods mRMR and IG, the SVM also obtains higher accuracies than all the 84 features.4) Different feature subsets lead to different forecast accuracies.

Even on time scales of a few days or less, uncertainties in the initial state of the atmosphere may lead to substantial forecast errors.

But whatever the subset is, SVM is superior to kNN and MAPLSC, especially on the subset of 9 features where SVM is better than MAPLSC, Naïve Bayes and kNN, and similar to WSVM. Figure 9 demonstrates that different feature subsets lead to different forecast accuracy.

Using model guidance and comparing the various forecast fields to climatology, extreme events such as excessive precipitation associated with later flood events lead to better forecasts.

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