Title
An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction.
Abstract
We consider the task of performing prediction with neural networks (NNs) on the basis of uncertain input data expressed in the form of intervals. We aim at quantifying the uncertainty in the prediction arising from both the input data and the prediction model. A multilayer perceptron NN is trained to map interval-valued input data onto interval outputs, representing the prediction intervals (PIs) of the real target values. The NN training is performed by nondominated sorting genetic algorithm-II, so that the PIs are optimized both in terms of accuracy (coverage probability) and dimension (width). Demonstration of the proposed method is given in two case studies: 1) a synthetic case study, in which the data have been generated with a 5-min time frequency from an autoregressive moving average model with either Gaussian or Chi-squared innovation distribution and 2) a real case study, in which experimental data consist of wind speed measurements with a time step of 1 h. Comparisons are given with a crisp (single-valued) approach. The results show that the crisp approach is less reliable than the interval-valued input approach in terms of capturing the variability in input.
Year
DOI
Venue
2015
10.1109/TNNLS.2015.2396933
IEEE transactions on neural networks and learning systems
Keywords
Field
DocType
uncertainty.,multi-objective genetic algorithm (moga),short-term wind speed forecasting,interval-valued neural networks (nns),prediction intervals (pis),sociology,artificial neural networks,statistics,wind speed,predictive models,uncertainty
Autoregressive–moving-average model,Uncertainty quantification,Pattern recognition,Computer science,Sorting,Prediction interval,Multilayer perceptron,Gaussian,Artificial intelligence,Artificial neural network,Coverage probability,Machine learning
Journal
Volume
Issue
ISSN
PP
99
2162-2388
Citations 
PageRank 
References 
4
0.40
24
Authors
3
Name
Order
Citations
PageRank
Ronay Ak1474.61
Valeria Vitelli2726.93
Enrico Zio31100145.38