Sentence examples for multiple forecasting from inspiring English sources

The proposed framework combines multiple forecasting models and adaptive machine learning techniques for information processing.

Multiple forecasting measures have been developed in literature, including least-square support vector machines (LS-SVM), neural network (NN), time-series based ARIMA model, etc.

In-sample and out-of-sample forecasting tests are used to examine the performance of the parcel-scale econometric and simulation models, and the importance of multiple forecasting challenges is assessed.

However, the false alarm rate necessarily increases when multiple forecasting methods are used simultaneously.

Local forecasters make forecasts and heat alerts based on multiple forecast products as well as their judgment based on their local knowledge of historical weather and other factors mentioned above.

Again, the use of multiple forecasts from slightly altered starting points was able to provide early warnings.

The proposed methodology can be extended to other forecast methods, especially when it comes to the availability of multiple forecast models.

Step 1 Form the n-dimensional dataset E = {e 1, e 2, …, e n } of prediction errors for multiple forecast horizons or wind farms using the historical data.

Numerous research studies in literature strongly recommend this approach, due to the fact that a combination of multiple forecasts almost always substantially reduces the overall forecasting errors as well as outperforms the component models.

Open image in new window Fig. 2 Mechanism sketch of entire modelling and simulation process Step 1 Form the n-dimensional dataset E = {e 1, e 2, …, e n } of prediction errors for multiple forecast horizons or wind farms using the historical data.

This approach analyzes multiple forecasts created with an individual forecast model or multiple models.