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

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 show...

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Bibliographic Details
Published in:The Artificial intelligence review 2014-02, Vol.41 (2), p.287-300
Main Authors: Faustino, Claudio Paulo, Novaes, Camila Paiva, Pinheiro, Carlos Alberto M., Carpinteiro, Otávio A.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Back propagation
Clustering
Computer Science
Expert systems
Forecasting
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Mathematical models
Neural networks
Neurons
Statistical methods
Time series
Variables
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Summary: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.
ISSN:0269-2821
1573-7462
DOI:10.1007/s10462-011-9308-9