PREDICTION INTERVAL ESTIMATION TECHNIQUES FOR EMPIRICAL MODELING STRATEGIES AND THEIR APPLICATIONS TO SIGNAL VALIDATION TASKS

2004 ◽  
Author(s):  
BRANDON RASMUSSEN ◽  
J. WESLEY HINES
Keyword(s):  
Prediction Interval ◽  
Interval Estimation ◽  
Empirical Modeling ◽  
Estimation Techniques ◽  
Signal Validation

Bootstrap prediction interval estimation for wind speed forecasting

2015 ◽  
Author(s):  
Rachid Errouissi ◽  
Julian Cardenas-Barrera ◽  
Julian Meng ◽  
Eduardo Castillo-Guerra ◽  
Xun Gong ◽  
...  
Keyword(s):  
Wind Speed ◽  
Prediction Interval ◽  
Interval Estimation ◽  
Wind Speed Forecasting

scholarly journals Evolutionary-based prediction interval estimation by blending solar radiation forecasting models using meteorological weather types

2021 ◽  
pp. 107531
Author(s):  
Inés M. Galván ◽  
Javier Huertas-Tato ◽  
Francisco J. Rodríguez-Benítez ◽  
Clara Arbizu-Barrena ◽  
David Pozo-Vázquez ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Prediction Interval ◽  
Interval Estimation ◽  
Weather Types ◽  
Forecasting Models

scholarly journals Prediction Interval Estimation Methods for Artificial Neural Network (ANN)-Based Modeling of the Hydro-Climatic Processes, a Review

2021 ◽  
Vol 13 (4) ◽  
pp. 1633
Author(s):  
Vahid Nourani ◽  
Nardin Jabbarian Paknezhad ◽  
Hitoshi Tanaka
Keyword(s):  
Sustainable Management ◽  
Review Paper ◽  
Prediction Interval ◽  
Interval Estimation ◽  
Estimation Methods ◽  
Future Studies ◽  
Pros And Cons ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Meta Analyses

Despite the wide applications of artificial neural networks (ANNs) in modeling hydro-climatic processes, quantification of the ANNs’ performance is a significant matter. Sustainable management of water resources requires information about the amount of uncertainty involved in the modeling results, which is a guide for proper decision making. Therefore, in recent years, uncertainty analysis of ANN modeling has attracted noticeable attention. Prediction intervals (PIs) are one of the prevalent tools for uncertainty quantification. This review paper has focused on the different techniques of PI development in the field of hydrology and climatology modeling. The implementation of each method was discussed, and their pros and cons were investigated. In addition, some suggestions are provided for future studies. This review paper was prepared via PRISMA (preferred reporting items for systematic reviews and meta-analyses) methodology.

Prediction interval estimation in transformed linear models

2001 ◽  
Vol 51 (4) ◽  
pp. 345-350 ◽  
Author(s):  
Kwanho Cho ◽  
In-Kwon Yeo ◽  
Richard A. Johnson ◽  
Wei-Yin Loh
Keyword(s):  
Linear Models ◽  
Prediction Interval ◽  
Interval Estimation
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