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Use of forecast models can help determine the magnitude and pattern of the rainfall expected.
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Using a consensus of forecast models reduces forecast error.
Using a consensus of forecast models, as well as ensemble members of the various models, can help reduce forecast error.
Estimation techniques based on different distribution methods have been used widely for estimating the exogenous variables of forecast models [5, 20].
The second main reason for the differences in forecasts in Fig. 1 is in the use of different forecast models.
It is imperative that any terms used in the development of forecasting models are heavily screened to address the complexities of the driving forces behind health-information seeking and routinely re-evaluated to account for any shifts in search behaviour which may occur [ 4].
14 The mathematical models included non-time varying parameters such as the reporting fraction of cases (proportion of malaria cases in a population that is reported to public health), average life expectancy and several vector characteristics, which are listed in table 4. Authors used different approaches to evaluate the accuracy of forecasting models.
Abramović [1] examined the use of demand forecasting models in international freight transport.
The combined use of monitoring and forecast models allows to identify these impacts and may play a relevant role in mitigation protocols.
The main advantage of this method is that it can produce high forecast rates using all types of numerical forecast models, even those that are not rate-based.
The Bureau of Meteorology began a method of forecasting rainfall using a combination, or ensemble, of different forecast models in 2006.
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