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An Interval Type-2 Fuzzy Neural Network for Chaotic Time Series Prediction with Cross-Validation and Akaike Test

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Soft Computing for Intelligent Control and Mobile Robotics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 318))

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Abstract

A novel homogeneous integration strategy of an interval type-2 fuzzy inference system (IT2FIS) with Takagi-Sugeno-Kang reasoning (TSK IT2FIS) is presented. This TSK IT2FIS is represented as an adaptive neural network (NN) with hybrid learning (IT2FNN:BP+RLS) in order to automatically generate an interval type-2 fuzzy logic system (TSK IT2FLS). Consequent parameters are updated with recursive least-square (RLS) algorithm; antecedent parameters with back-propagation (BP) algorithm. Mackey-Glass chaotic time series forecasting results are presented ((=17, 30, 100) with different signal noise ratio (SNR). Soundness for uncertainty, adaptability and learning and generalization capabilities is shown using 10-fold Cross Validation, Akaike Information Criteria (AIC) and F-Test.

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Author information

Authors and Affiliations

  1. Computer Science in the Universidad Autonoma de Baja California, Tijuana, B. C., México

    Juan R. Castro, Olivia Mendoza & Antonio Rodríguez-Díaz

  2. Computer Science in the Graduate Division Tijuana, Institute of Technology Tijuana, B.C., Mexico

    Oscar Castillo & Patricia Melin

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  1. Juan R. Castro
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  2. Oscar Castillo
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  3. Patricia Melin
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  4. Olivia Mendoza
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  5. Antonio Rodríguez-Díaz
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Editor information

Editors and Affiliations

  1. Tijuana Institute of Technology, Chula Vista, CA, USA

    Oscar Castillo

  2. Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

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Castro, J.R., Castillo, O., Melin, P., Mendoza, O., Rodríguez-Díaz, A. (2010). An Interval Type-2 Fuzzy Neural Network for Chaotic Time Series Prediction with Cross-Validation and Akaike Test. In: Castillo, O., Kacprzyk, J., Pedrycz, W. (eds) Soft Computing for Intelligent Control and Mobile Robotics. Studies in Computational Intelligence, vol 318. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15534-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-15534-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15533-8

  • Online ISBN: 978-3-642-15534-5

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