An enhanced version of the hybrid ensemble-3DVAR data assimilation system for the WRF model is applied to the assimilation of radial velocity (Vr) data from two coastal WSR-88D radars for the prediction of Hurricane Ike (2008) before and during its landfall. In this hybrid system, flow-dependent ensemble covariance is incorporated into the varitional cost function using the extended control var...

3 Introduction Introduction This paper presents a hybrid intelligent system for This paper presents a hybrid intelligent system for electrical load forecast, named by PREVER. electrical load forecast, named by PREVER. Artificial Neural Networks (ANN) were combined with Artificial Neural Networks (ANN) were combined with Heuristic Rules to create the system. Heuristic Rules to create the system....

This paper investigates a range of statistical, neural network and hybrid approaches for making one-step-ahead forecasts of a monthly water demand time-series on the basis of 108 historical data points. A uni-variate approach, using solely the water demand time-series, is taken to construct two stand-alone forecasting models: a backpropagation network and a statistical model. A bi-variate appro...

—The sibling model is often one of the best methods for calculating preseason forecasts of adult return abundance (recruits) for populations of Pacific salmon Oncorhynchus spp. This model forecasts abundance of a given age-class for a given year based on the abundance of the previous age-class in the previous year. When sibling relations fit historical data well, the sibling model generally per...

Accurate and reliable forecasts of diarrhea incidences are necessary for the health authorities to ensure the appropriate action for the control of the outbreak. In this paper, a novel hybrid model known as EEMD-GRNN is proposed to forecast the diarrhea incidences. The proposed approach first uses Ensemble Empirical Mode Decomposition (EEMD), which can adaptively decompose the complicated raw t...

We present a forecast-based adaptive management framework for water supply reservoirs and evaluate the contribution of long-term inflow forecasts to reservoir operations. Our framework is developed for snow-dominated river basins that demonstrate large gaps in forecast skill between seasonal and inter-annual time horizons. We quantify and bound the contribution of seasonal and inter-annual fore...

We present an on-line management strategy for photovoltaic-hydrogen (PV-H2) hybrid energy systems. The strategy follows a receding-horizon principle and exploits solar radiation forecasts and statistics generated through a Gaussian process model. We demonstrate that incorporating forecast information can dramatically improve the reliability and economic performance of these promising energy pro...

accurate quantitative precipitation forecasts (qpfs) have been always a demanding and challenging job in numerical weather prediction (nwp). the outputs of ensemble prediction systems (epss) in the form of probability forecasts provide a valuable tool for probabilistic quantitative precipitation forecasts (pqpfs). in this research, different configurations of wrf and mm5 meso-scale models form ...