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

This 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 w...

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Veröffentlicht in:International journal of general systems 2011-04, Vol.40 (3), p.263-282
Hauptverfasser: López, Josefina, Cellier, François E., Cembrano, Gabriela
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container_issue 3
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container_title International journal of general systems
container_volume 40
creator López, Josefina
Cellier, François E.
Cembrano, Gabriela
description This 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.
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subjects Aplicacions de la informàtica
Aplicacions informàtiques a la física i l‘enginyeria
Assessments
Demand
Estimating
Estimating techniques
estimation of predictability horizon
fuzzy inductive reasoning
Fuzzy logic
Fuzzy systems
inductive modelling
Informàtica
Marketing
Mathematical models
Modelling
Models matemàtics
Predictions
Sistemes borrosos
Time series
time-series prediction
Àrees temàtiques de la UPC
title Estimating the horizon of predictability in time-series predictions using inductive modelling tools
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