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Soliton wave parameter estimation with the help of artificial neural network by using the experimental data carried out on the nonlinear transmission line

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  • Aksoy, Abdullah
  • Yenikaya, Sibel

Abstract

In this study, an artificial neural network (ANN) model is generated, which is used to estimate the output parameters of soliton waves produced as a result of nonlinear transmission lines (NLTLs). Three different output parameters are acquired as a consequence of the experiments carried out utilizing the five various input parameters that are set in the ANN-based study. Input parameters for NLTL designs with 116 different experiments; inductor (L), input voltage (Vi) value, number of nodes (n), capacitance (C(V)) and load resistance (RLoad) values. Output parameters values, which are maximum voltage (Vmax), center frequency (fcenter), and voltage modulation depth (VMD). Input and output data; 70 % is set aside for training, 15 % for validation and the remaining 15 % for testing. Training, validation, and testing steps are repeated for the output parameters, in which case more than 99 % correlation is found as a result of each operation. An absolute percentage error value is found for each output parameter. Moreover, Mean absolute percentage error (MAPE) is calculated for these output datasets. The data set is tested for the experimental studies carried out in the literature, and it is observed that there is a compliance of over 99 % for this situation.

Suggested Citation

  • Aksoy, Abdullah & Yenikaya, Sibel, 2023. "Soliton wave parameter estimation with the help of artificial neural network by using the experimental data carried out on the nonlinear transmission line," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    • Handle: RePEc:eee:chsofr:v:169:y:2023:i:c:s0960077923001273
    DOI: 10.1016/j.chaos.2023.113226
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    References listed on IDEAS

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    1. El-Ganaini, Shoukry & Kumar, Hitender, 2020. "A variety of new traveling and localized solitary wave solutions of a nonlinear model describing the nonlinear low- pass electrical transmission lines," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Kudryashov, Nikolai A., 2005. "Simplest equation method to look for exact solutions of nonlinear differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 24(5), pages 1217-1231.
    3. Guy Roger Deffo & Serge Bruno Yamgoue & Francois Beceau Pelap, 2018. "Modulational instability and peak solitary wave in a discrete nonlinear electrical transmission line described by the modified extended nonlinear Schrödinger equation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 91(10), pages 1-9, October.
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    Cited by:

    1. Aksoy, Abdullah & Yigit, Enes, 2023. "Automatic soliton wave recognition using deep learning algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

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