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Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio...
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Ying Li and Samuel N. Stechmann
Intuitively, one would expect a more skillful forecast if predicting weather averaged over one week instead of the weather averaged over one day, and similarly for different spatial averaging areas. However, there are few systematic studies of averaging ...
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Rahul Pathak and Daniel Williams
The sudden onset of the COVID-19 pandemic posed significant challenges for forecasting professionals worldwide. This article examines the early forecasts of COVID-19 transmission, using the context of the United States, one of the early epicenters of the...
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Pieter Cawood and Terence Van Zyl
The techniques of hybridisation and ensemble learning are popular model fusion techniques for improving the predictive power of forecasting methods. With limited research that instigates combining these two promising approaches, this paper focuses on the...
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Lucky O. Daniel, Caston Sigauke, Colin Chibaya and Rendani Mbuvha
Wind offers an environmentally sustainable energy resource that has seen increasing global adoption in recent years. However, its intermittent, unstable and stochastic nature hampers its representation among other renewable energy sources. This work addr...
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Aldo S. Moya-Álvarez, José Gálvez, Andrea Holguín, René Estevan, Shailendra Kumar, Elver Villalobos, Daniel Martínez-Castro and Yamina Silva
The ability of the WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to forecast extreme rainfall in the Central Andes of Peru is evaluated in this study, using observations from stations located in the Mantaro basin and GOES (Geosta...
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Rudy Gargano, Carla Tricarico, Francesco Granata, Simone Santopietro and Giovanni De Marinis
Peak water demand is one of the most stringent operative conditions for a Water Distribution System (WDS), not only for the intensity of the event itself, but also for its recurring nature. The estimation of the maximum water demand is a crucial aspect i...
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Bo Qu, Xingnan Zhang, Florian Pappenberger, Tao Zhang, Yuanhao Fang
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Statistical post-processing for multi-model grand ensemble (GE) hydrologic predictions is necessary, in order to achieve more accurate and reliable probabilistic forecasts. This paper presents a case study which applies Bayesian model averaging (BMA) to ...
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