Time series forecasting through rule-based models obtained via rough sets

Authors:
Claudio Paulo Faustino;Carlos Alberto Pinheiro;Otávio A. Carpinteiro;Isaias Lima
Affiliations:
Research Group on Systems and Computer Engineering, Federal University of Itabubá, Itajubá, Brazil 37500-903;Research Group on Systems and Computer Engineering, Federal University of Itabubá, Itajubá, Brazil 37500-903;Research Group on Systems and Computer Engineering, Federal University of Itabubá, Itajubá, Brazil 37500-903;Research Group on Systems and Computer Engineering, Federal University of Itabubá, Itajubá, Brazil 37500-903
Venue:
Artificial Intelligence Review
Year:
2011

Citing 4
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Abstract

Prediction models based on artificial intelligence techniques have been widely used in Time Series Forecasting in several areas. They are often fuzzy models or neural networks. However, the use of rough sets based models have not yet been explored. The aim of this work is to introduce a new approach which uses rough set concepts to obtain rule-based models capable to perform time series forecasting.