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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 ...
Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
Spatial load forecasting using a demand propagation approach
(2011-05-31)
A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses ...
Top-down strategies based on adaptive fuzzy rule-based systems for daily time series forecasting
(Elsevier Science BvAmsterdamHolanda, 2011)
Statistical post-processing of ensemble forecasts of temperature in Santiago de Chile
(John Wiley and Sons Ltd, 2020)
Modelling forecast uncertainty is a difficult task in any forecasting problem. In weather forecasting a possible solution is the use of forecast ensembles, which are obtained from multiple runs of numerical weather prediction ...
Data Issues in Spatial Electric Load Forecasting
(Ieee, 2014-01-01)
The magnitude and geographic location of electricity demand in the planning horizon are vital pieces of information for power distribution companies in planning future network expansion and operation. Such information is ...
On predicting wind power series by using Bayesian Enhanced modified based-neural network
(Institute of Electrical and Electronics Engineers Inc., 2017)
In this paper, wind power series prediction using BEA modified (BEAmod.) neural networks-based approach is presented. Wind power forecasting is a complex, multidimensional, and highly non-linear system. Neural network is ...