Add to ORKGOver the years, several studies that compare individual forecasts with the combination of forecasts were published. There is, however, no unanimity in the conclusions. Furthermore, methods of combination by regression are poorly explored. This paper presents a comparative study of three methods of combination and their individual forecasts. Based on simulated data, it is evaluated the accuracy of Artificial Neural Networks, ARIMA and exponential smoothing models; calculating the combined forecasts through simple average, minimum variance and regression methods. Four accuracy measurements, MAE, MAPE, RMSE and Theil’s U, were used for choosing the most accurate method. The main contribution is the accuracy of the combination by regression met...
To improve the forecasting accuracies, researchers have long been using various combination techniqu...
In this chapter, we evaluate the forecasting performance of the model combination and forecast combi...
Time series forecasting has a long track record in many application areas. In forecasting research, ...
Over the years, several studies that compare individual forecasts with the combination of forecasts ...
A necessidade de realizar previsões acuradas, oriunda do crescente aprimoramento tecnológico, tem es...
Abstract Combining forecasts can be based on different data or different methods or both. In practic...
This thesis evaluates four of the most popular methods for combining time series forecasts. One aspe...
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, ...
This thesis presents and evaluates nineteen methods for combining up to eleven automated univariate ...
An accurate forecast about the future is vital in time series analysis, butit is always challenging ...
Many researchers have argued that combining many models for forecasting gives better estimates than ...
Effective and efficient planning in various areas can be significantly supported by forecasting a va...
Many researchers have argued that combining many models for forecasting gives better estimates than ...
This article compared single to combined forecasts of wind run using artificial neural networks, dec...
Demand forecasting is a major factor for the efficiency of the management of organizations, directly...
To improve the forecasting accuracies, researchers have long been using various combination techniqu...
In this chapter, we evaluate the forecasting performance of the model combination and forecast combi...
Time series forecasting has a long track record in many application areas. In forecasting research, ...
Over the years, several studies that compare individual forecasts with the combination of forecasts ...
A necessidade de realizar previsões acuradas, oriunda do crescente aprimoramento tecnológico, tem es...
Abstract Combining forecasts can be based on different data or different methods or both. In practic...
This thesis evaluates four of the most popular methods for combining time series forecasts. One aspe...
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, ...
This thesis presents and evaluates nineteen methods for combining up to eleven automated univariate ...
An accurate forecast about the future is vital in time series analysis, butit is always challenging ...
Many researchers have argued that combining many models for forecasting gives better estimates than ...
Effective and efficient planning in various areas can be significantly supported by forecasting a va...
Many researchers have argued that combining many models for forecasting gives better estimates than ...
This article compared single to combined forecasts of wind run using artificial neural networks, dec...
Demand forecasting is a major factor for the efficiency of the management of organizations, directly...
To improve the forecasting accuracies, researchers have long been using various combination techniqu...
In this chapter, we evaluate the forecasting performance of the model combination and forecast combi...
Time series forecasting has a long track record in many application areas. In forecasting research, ...