Price forecast is a task challenging and very important in competitive electricity market context. Both market players and regulators concern very much about the price evolution, on one hand, the prediction of the market price is a crucial information for the production arrangement and bidding strategies. On the other hand, the regulators need to analyze the market behavior and monitor the mark...

The Southeast Alaska Coastal Monitoring (SECM) project has been sampling juvenile salmon (Oncorhynchus spp.) and associated biophysical parameters in northern Southeast Alaska (SEAK) annually since 1997 to better understand effects of environmental change on salmon production. A pragmatic application of the annual sampling effort is to forecast the abundance of adult salmon returns in subsequen...

In view of the limitations of single forecast model, forecasted results of different models will have some differences, in order to improve the forecast precision and the forecast results reliability, on the basis of determining the single forecast model for total power of China’s agricultural machinery, the nonlinear combined forecast model for total power of agricultural machinery was establi...

We present ongoing work on a model-driven decision support system (DSS) that is aimed at providing guidance on reflecting and adjusting judgmental forecasts. We consider judgmental forecasts of cash flows generated by local experts in numerous subsidiaries of an international corporation. Forecasts are generated in a decentralized, non-standardized fashion, and corporate managers and controller...

An ensemble local hydrologic forecast derived from the seasonal forecasts of the International Research Institute for Climate Prediction (IRI) is presented. Three-month seasonal forecasts were used to resample historical meteorological conditions and generate ensemble forcing datasets for a TOPMODEL-based hydrology model. Eleven retrospective forecasts were run at Florida and New York sites. Fo...

Experiments were conducted to quantify the impact of satellite data (Earth Observations from Space—EOS) on the determination of current and future atmospheric state. These experiments have examined two different time periods using two different operational forecast models. The results show that, in the southern hemisphere, the accuracy of a no-satellite data 24-hour (one day) forecast is of the...

Forecast rationality under squared error loss implies various bounds on second moments of the data across forecast horizons. For example, the mean squared forecast error should be increasing in the horizon, and the mean squared forecast should be decreasing in the horizon. We propose rationality tests based on these restrictions, including new ones that can be conducted without data on the targ...

In this paper we use 4 different time series models to forecast sales in a goods management system. We use a variety of forecast combining techniques and measure the forecast quality by applying symmetric and asymmetric forecast quality measures. Simple, rank-, and criteria-based combining methods lead to an improvement of the individual time series models.