Results 231 to 240 of about 10,696 (267)

Seasonal forecasting of dissolved organic carbon in a Mediterranean catchment: Enhancing upstream control of disinfection by-product precursors. [PDF]

Environ Monit Assess
Pedregal-Montes A, Mercado-Bettín D, Futter M, Ledesma JLJ, Farré MJ, Marcé R, Jennings E.   +6 more
europepmc   +1 more source

FaXNet: a frequency-adaptive, explainable, and uncertainty-aware network for influenza forecasting. [PDF]

Front Public Health
He W, Li X, Liang X, Liu Z, Zeng Z, Yang Z, Hon C.   +6 more
europepmc   +1 more source

Protocol-aware epidemic forecasting across heterogeneous public health surveillance systems. [PDF]

Front Public Health
Hu Y, Han J, Liu M.
europepmc   +1 more source

Physics-guided networks for probabilistic hydrodynamic forecasting in canal systems. [PDF]

Environ Sci Ecotechnol
Liu W, Guan G, Chen X, Shi L, Fu G, Savic D.   +5 more
europepmc   +1 more source

Applied probabilistic forecasting

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Herding in Probabilistic Forecasts

Management Science, 2020
Decision makers often ask experts to forecast a future state. Experts, however, can be biased. In the economics and psychology literature, one extensively studied behavioral bias is called herding. Under strong levels of herding, disclosure of public information may lower forecasting accuracy.
Yanwei Jia, Jussi Keppo, Ville A. Satopää   +2 more
openaire   +1 more source

Probabilistic Networks as Probabilistic Forecasters

2003
To establish its clinical value, a probabilistic network is typically subjected to an evaluation study using real patient data from the field of application. The results of such a study are often summarised in the percentage of correctly predicted outcomes. In this paper, we propose the use of a forecasting score as an alternative way of expressing the
Linda C. van der Gaag, Silja Renooij
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Probabilistic demand forecasting at scale

Proceedings of the VLDB Endowment, 2017
We present a platform built on large-scale, data-centric machine learning (ML) approaches, whose particular focus is demand forecasting in retail. At its core, this platform enables the training and application of probabilistic demand forecasting models, and provides convenient abstractions and support functionality
Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang 0001   +8 more
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Wind Field Probabilistic Forecasting

2018
129
Oliver, Albert, Rodríguez, Eduardo, Mazorra-Aguiar, Luis   +2 more
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Probabilistic Load Forecasting

2021
Probabilistic load forecasting (PLF) is able to present the uncertainty information of the future loads. It is the basis of stochastic power system planning and operation. Recent works on PLF mainly focus on how to develop and combine forecasting models; while the feature selection issue has not been thoroughly investigated for PLF.
Qixin Chen, Hongye Guo, Kedi Zheng, Yi Wang   +3 more
openaire   +1 more source