In such learning, each network's forecasts are compared with the known correct answer and the weights are adjusted based on the resulting forecast error to minimize the error function.
The regression, a causal forecasting model that fits curves to the entire data set to minimize the forecasting errors, is often applied for the seasonal forecasting of tropical cyclones (TCs).
Recent advances in seasonal forecasting are generating new opportunities to minimize the impact of CV on health [ World Health Organization (WHO) 2004].
Operational systems to forecast storm surges are necessary to minimize their potential negative impacts on a wide range of coastal and maritime facilities, such as residences, coastal defenses, shipping, fisheries, offshore mining and others.
The ability to accurately forecast SLEV epidemics is needed to minimize human health risks and focus vector control efforts.
The coefficient α was chosen to minimize the forecast error variance in the training data, and was approximately 0.2 in all training cases.
When monitoring complaint levels over multi-year time frames, it is necessary to periodically update baseline model coefficients in order to minimize the extrapolation in forecasting.
It is critical that such predictions are robust and based on the best available statistical modeling approaches to minimize possible errors in the forecasts.
The basic science is well understood, it noted, but forecasting the hazard from induced earthquakes and taking steps to minimize the risk have been frustrated by the dearth of detailed geologic and geophysical observations of specific sites.
Discussions with stakeholders (Dewhurst, [2007]) emphasized that weather forecasts were used by stakeholders on an operational level, but mostly to minimize danger due to high winds and high seas rather than to forecast ice movement.
