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2014 | OriginalPaper | Buchkapitel

Genetic Optimization of Type-2 Fuzzy Integrators in Ensembles of ANFIS Models for Time Series Prediction

verfasst von : Jesus Soto, Patricia Melin

Erschienen in: Recent Advances on Hybrid Approaches for Designing Intelligent Systems

Verlag: Springer International Publishing

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Abstract

This chapter describes the genetic optimization of interval type-2 fuzzy integrators in Ensembles of ANFIS (adaptive neuro-fuzzy inferences systems) models for the prediction of the Mackey-Glass time series. The considered a chaotic system is he Mackey-Glass time series that is generated from the differential equations, so this benchmarks time series is used for the test of performance of the proposed ensemble architecture. We used the interval type-2 and type-1 fuzzy systems to integrate the output (forecast) of each Ensemble of ANFIS models. Genetic Algorithms (GAs) were used for the optimization of memberships function parameters of each interval type-2 fuzzy integrators. In the experiments we optimized Gaussians, Generalized Bell and Triangular membership functions for each of the fuzzy integrators, thereby increasing the complexity of the training. Simulation results show the effectiveness of the proposed approach.

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Titel: Genetic Optimization of Type-2 Fuzzy Integrators in Ensembles of ANFIS Models for Time Series Prediction
verfasst von: Jesus Soto
Patricia Melin
Verlag: Springer International Publishing
Buch: Recent Advances on Hybrid Approaches for Designing Intelligent Systems
Print ISBN: 978-3-319-05169-7

Electronic ISBN: 978-3-319-05170-3

Copyright-Jahr: 2014
DOI: https://doi.org/10.1007/978-3-319-05170-3_6

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