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Evaluation of Metaheuristics in the Optimization of Laguerre-Volterra Networks for Nonlinear Dynamic System Identification

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Intelligent Systems (BRACIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12319))

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Abstract

The main objective of nonlinear dynamic system identification is to model the behaviour of the systems under analysis from input-output signals. To approach this problem, the Laguerre-Volterra network architecture combines the connectionist approach with Volterra-based processing to achieve good performance when modeling high-order nonlinearities, while retaining interpretability of the system’s characteristics. In this research we assess the performances of three metaheuristics in the optimization of Laguerre-Volterra Networks using synthetic input-output data, a task in which only the simulated annealing metaheuristic was previously evaluated.

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Authors and Affiliations

  1. Department of Applied Computing, Federal University of Santa Maria, Santa Maria, 97105-900, Brazil

    Victor O. Costa & Felipe M. Müller

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  1. Victor O. Costa
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  2. Felipe M. Müller
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Correspondence to Victor O. Costa .

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Editors and Affiliations

  1. Federal University of São Carlos, São Carlos, Brazil

    Ricardo Cerri

  2. Federal University of ABC, Santo Andre, Brazil

    Ronaldo C. Prati

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Costa, V.O., Müller, F.M. (2020). Evaluation of Metaheuristics in the Optimization of Laguerre-Volterra Networks for Nonlinear Dynamic System Identification. In: Cerri, R., Prati, R.C. (eds) Intelligent Systems. BRACIS 2020. Lecture Notes in Computer Science(), vol 12319. Springer, Cham. https://doi.org/10.1007/978-3-030-61377-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-61377-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61376-1

  • Online ISBN: 978-3-030-61377-8

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