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Título

Estimating the horizon of predictability in time-series predictions using inductive modelling tools

AutorLópez, Josefina; Cellier, François E.; Cembrano, Gabriela CSIC ORCID
Palabras claveFuzzy inductive reasoning
Estimation of predictability horizon
Time\-series prediction
Inductive modelling
Fecha de publicación2011
EditorTaylor & Francis
CitaciónInternational Journal of General Systems 40(3): 263-282 (2011)
ResumenThis paper deals with the assessment of how far into the future a time series can be safely predicted using inductive modelling and extrapolation techniques. Three different time series are used to demonstrate the viability of the approaches presented in the paper: one time series representing the water demand of the city of Barcelona, another characterizing the water demand of a section of the city of Rotterdam, and a third describing weather data for the city of Tucson. Fuzzy inductive reasoning (FIR) is used to predict future values of these time series on the basis of their own past. FIR predictions come with two different built-in measures of confidence that can be used to obtain a quantitative estimate of how far into the future a time series can be predicted.
Versión del editorhttp://dx.doi.org/10.1080/03081079.2010.536540
URIhttp://hdl.handle.net/10261/96804
DOI10.1080/03081079.2010.536540
Identificadoresdoi: 10.1080/03081079.2010.536540
issn: 0308-1079
e-issn: 1563-5104
Aparece en las colecciones: (IRII) Artículos




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