Improving the performance of fuzzy rules-based forecasters through application of FCM algorithm

Authors:
Claudio Paulo Faustino;Camila Paiva Novaes;Carlos Alberto Pinheiro;Otávio A. Carpinteiro
Affiliations:
Research Group on Systems and Computer Engineering, Federal University of Itajubá, Itajubá, Brazil 37500-903;Division of Astrophysics, National Institute of Spacial Research (INPE), São José dos Campos, Brazil 12227-010;Research Group on Systems and Computer Engineering, Federal University of Itajubá, Itajubá, Brazil 37500-903;Research Group on Systems and Computer Engineering, Federal University of Itajubá, Itajubá, Brazil 37500-903
Venue:
Artificial Intelligence Review
Year:
2014

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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. This paper describes the development of neural and fuzzy models for forecasting time series of practical examples, and shows the comparisons of results between models, including the results of statistical modeling. The use of data clustering algorithms like Fuzzy C-Means is considered in fuzzy models.