develop next day total energy use (NDTEU) and next day peak demand (NDPD) forecast models for each phase. The models were ….87 and forecast accuracy ranged from 0.74 to 0.84. NDPD hindcast accuracy ranged from 0.68 to 0.74 and forecast accuracy … combined the best traits of the ARIMAX and NN techniques, resulting in improved hindcast and forecast fits across the all three …

against a control algorithm with a perfect forecast. A specific case study, using storage on the LV network, is presented, and …

The forecast plays an important role in the planning, the decision-making and control in any domain of activity … (univariate models), that use only the information of its past values to forecast the future, can often predict future with more … accuracy than causal or multivariate models. In this paper, we model and forecast the offensive effectiveness of the soccer …

In nonlinear econometric models, the evaluation of forecast errors is usually performed, completely or partially, by … one-period (static) forecast errors empirically. …

An empirical forecast accuracy comparison of the non-parametric method, known as multivariate Nearest Neighbor method …, through the estimation of economic indicators plugged in the bridge equations, we get more accurate forecasts when using … for dependent time series, providing confidence intervals for point forecast in time series. …

variables: the Greek unemployment rate and the FTSE-100 stock index returns. The methodology employed in the effort to forecast …

realised inflation with the stated ex ante coverage probabilities 50, 75 and 90 percent? In total 150 interval forecast 1999:Q2 …-2005:Q2 are assessed for CPI and KPIX. The main result is that the forecast uncertainty is understated, but there are … substantial differences between individual forecast origins and inflation measures. …