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Efficient Error Based Metrics for Fuzzy-Neural Network Performance Evaluation

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Advanced Computing in Industrial Mathematics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 728))

Abstract

In this paper the effectiveness of different error metrics for assessment of the capabilities of an advanced fuzzy-neural architecture are studied. The proposed structure combines the potentials of the Intuitionistic Fuzzy Logic with the simplicity of the Neo-Fuzzy Neuron theory for implementation of robust modeling mechanisms, able to capture uncertain variations in the data space. A major concern when evaluating the performance of such kind of models is the selection of appropriate error metrics in order to assess their potential to capture a wide range of system behaviours. Therefore, different error metrics to evaluate the functional properties of a proposed Intuitionistic Neo-fuzzy network are studied and a comparative analysis in modeling of chaotic time series is made.

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Author information

Authors and Affiliations

  1. Department of Informatics and Statistics, University of Food Technologies, 26 Maritza blvd., 4000, Plovdiv, Bulgaria

    Margarita Terziyska & Maria Dobreva

  2. Department of Chemical and Metallurgical Engineering, Laboratory of Automation and Process Control, Aalto University, Kemistintie 1, 02150, Espoo, Finland

    Yancho Todorov

Authors
  1. Margarita Terziyska
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  2. Yancho Todorov
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  3. Maria Dobreva
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Corresponding author

Correspondence to Yancho Todorov .

Editor information

Editors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Science, Sofia, Bulgaria

    Krassimir Georgiev

  2. Faculty of Applied Mathematics and Informatics, Technical University of Sofia, Sofia, Bulgaria

    Michail Todorov

  3. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Ivan Georgiev

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Terziyska, M., Todorov, Y., Dobreva, M. (2018). Efficient Error Based Metrics for Fuzzy-Neural Network Performance Evaluation. In: Georgiev, K., Todorov, M., Georgiev, I. (eds) Advanced Computing in Industrial Mathematics. Studies in Computational Intelligence, vol 728. Springer, Cham. https://doi.org/10.1007/978-3-319-65530-7_17

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  • DOI: https://doi.org/10.1007/978-3-319-65530-7_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65529-1

  • Online ISBN: 978-3-319-65530-7

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