Results 31 to 40 of about 10,696 (267)
Probabilistic Weather Forecasting in R [PDF]
The R Journal, 2011 Abstract This article describes two R packages for probabilistic weather forecasting, ensembleBMA, which offers ensemble postprocessing via Bayesian model averaging (BMA), and ProbForecastGOP, which implements the geostatistical output perturbation (GOP) method. BMA forecasting models use mixture distributions, in which each component corresponds to an
Chris Fraley +4 more
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Embedding based quantile regression neural network for probabilistic load forecasting
Journal of Modern Power Systems and Clean Energy, 2018 Compared to traditional point load forecasting, probabilistic load forecasting (PLF) has great significance in advanced system scheduling and planning with higher reliability.
Dahua GAN +3 more
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Probabilistic photovoltaic power forecasting model based on deterministic forecasts [PDF]
E3S Web of Conferences, 2020 This paper presents an original probabilistic photovoltaic (PV) power forecasting model for the day-ahead hourly generation in a PV plant. The probabilistic forecasting model is based on 12 deterministic models developed with different techniques.
Fernandez-Jimenez L. Alfredo +4 more
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Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps [PDF]
Hydrology and Earth System Sciences, 2023 Real-time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. However, we are now witnessing an increasing number of studies aimed at also including flood mapping as ...
V. Jean +3 more
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Probabilistic Load Forecasting With Reservoir Computing
IEEE Access, 2023 Some applications of deep learning require not only to provide accurate results but also to quantify the amount of confidence in their prediction. The management of an electric power grid is one of these cases: to avoid risky scenarios, decision-makers need both precise and reliable forecasts of, for example, power loads.
Michele Guerra +2 more
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Applied Sciences, 2019 Precise prediction of short-term electric load demand is the key for developing power market strategies. Due to the dynamic environment of short-term load forecasting, probabilistic forecasting has become the center of attention for its ability of ...
Zhengmin Kong +3 more
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Probabilistic forecasting of wind power production losses in cold climates: a case study [PDF]
Wind Energy Science, 2018 The problem of icing on wind turbines in cold climates is addressed using probabilistic forecasting to improve next-day forecasts of icing and related production losses.
J. Molinder +4 more
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DYNAMIC PROBABILISTIC FORECASTING WITH UNCERTAINTY
International Journal of Theoretical and Applied Finance, 2019 In this paper, we introduce a dynamical model for the time evolution of probability density functions incorporating uncertainty in the parameters. The uncertainty follows stochastic processes, thereby defining a new class of stochastic processes with values in the space of probability densities.
Benth, Fred Espen +2 more
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Parameter-efficient deep probabilistic forecasting
International Journal of Forecasting, 2023 Probabilistic time series forecasting is crucial in many application domains such as retail, ecommerce, finance, or biology. With the increasing availability of large volumes of data, a number of neural architectures have been proposed for this problem.
Sprangers, O. +2 more
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Probabilistic Forecasting of Sensory Data With Generative Adversarial Networks – ForGAN
IEEE Access, 2019 Time series forecasting is one of the challenging problems for humankind. The traditional forecasting methods using mean regression models have severe shortcomings in reflecting real-world fluctuations.
Alireza Koochali +3 more
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