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Better forecasting accuracy: Sales leader judgment can be an important ingredient in forecasting deals, but human judgment often fares far worse than analytical models in assessing the likely outcome of deals and sales teams.
The proposed forecasting approach gives better forecasting accuracy: the MAPE has 8.1133% average value.
In another aspect, Azizi [1] shows that ANFIS model provides better forecasting accuracy in comparison with Bayesian model.
The proposed forecasting approach with input-data subset #5 gives better forecasting accuracy: the MAPE has 8.1133% average value.
However, in absolute terms, the univariate models have better forecasting accuracy with respect to short term horizons.
They found that GARCH 1, 1) with GED had better forecasting accuracy compared to that using Student's t-distribution.
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Empirical results from eight real-world time series show that our approach provides significantly better forecasting accuracies than the component models and other well recognized linear combination schemes.
Results from the study show that the Reg-SARIMA GARCH model pReg-SARIMA GARCHorecast accuracy with a modelabsolute produceserror (MAPE) of 1.42%.
Unfortunately, however, it is not always easy to investigate whether such a declustering-based RI algorithm has poorer or better forecast accuracy.
begin{aligned} MAE=, & frac{sum limits _{i=1}^N |y_i-widehat{y_i}|}{N} end{aligned} (1) begin{aligned} MAPE=, & frac{sum limits _{i=1}^N |y_i-widehat{y_i}|}{N} times 100% end{aligned} (2 Smaller values of the MAE and MAPE indicate better forecast accuracy.
Elsharkawy (1998) showed that radial basis function type neural network model had better forecast accuracy than the conventional methods in terms of predicting the oil formation volume factor, solution gas oil ratio, oil viscosity, saturated oil density, under-saturated oil compressibility, and evolved gas gravity.
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