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Physics‐based forecasts of equatorial radio scintillation for the Communication and Navigation Outage Forecasting System (C/NOFS)
(American Geophysical Union, 2005-12-28)
The plans for producing long‐term (6–24 hour) forecasts of equatorial plasma structure and radio scintillation for the Communication and Navigation Outage Forecasting System (C/NOFS) program are described. We discuss the ...
Cross-validation based forecasting method: a machine learning approach
(2019-02)
Our paper aims to evaluate two novel methods on selecting the best forecasting model or its combination based on a Machine Learning approach. The methods are based on the selection of the ”best” model, or combination of ...
New indices for the spatial validation of plume forecasts with observations of smoke plumes from grassfires
(Elsevier, 2013-03)
The purpose of this work is to propose new indices for the spatial validation of hazardous plumes forecast, and apply and test them with data of a case study. One, the Plume-Overlap-Area Hit index, is a modification of a ...
Validation of a Statistical Forecast Model for Zonda Wind in West Argentina Based on the Vertical Atmospheric Structure
(Scientific Research, 2016-01)
Zonda is a strong, warm, very dry wind associated with adiabatic compression upon descending the eastern slopes of the Andes Cordillera in western-central Argentina. This research seeks, first, to validate the skill of a ...
Intraseasonal Ensemble Forecasting for the Brazilian Northeastern
(Universidade Federal de Santa Maria, 2019)
Top-down strategies based on adaptive fuzzy rule-based systems for daily time series forecasting
(Elsevier Science BvAmsterdamHolanda, 2011)
Forecasting energy time-series data using a fuzzy ARTMAP neural network
(2020-10-14)
Time-series forecasting is an important field of machine learning and is fundamental in analyzing trends based on historical data from various sources. In this paper, a fuzzy ARTMAP neural network for time-series forecasting ...
An explainable machine learning model to optimize demand forecasting in Company DEOS
(Universidad de LimaPE, 2023)
Nowadays, having an accurate demand forecast is extremely important as it allows the company to manage resources in an optimal way and thus achieve greater productivity. There is a large demand for accurate forecasting, ...
T-fold sequential-validation technique for out-of-distribution generalization with financial time series data
(International Conference on Econometrics and Statistics, 2021-06)
T-fold sequential-validation technique for out-of-distribution generalization with financial time series data
(International Conference on Econometrics and Statistics, 2021-06)