Sergienko D.F. Comparative analysis of neural network methods for solving the model of a single dislocation source of geoacoustic emission
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https://doi.org/10.15688/mpcm.jvolsu.2026.2.4
Darya F. Sergienko
Junior Researcher, at the Laboratory of Acoustic Research; 3-Year Postgraduate Student, at the Department of Computer Science and Mathematics, Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences; Vitus Bering Kamchatka State University
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https://orcid.org/0000-0002-7915-121Xhttps://orcid.org/0009-0008-6512-4537
Mirnaya St, 7, 684034 Paratunka, Russian Federation; Pogranichnaya St, 4, 683032 Petropavlovsk-Kamchatsky, Russian Federation
Abstract. This paper presents a comparative analysis of computational methods for modeling a single dislocation source of geoacoustic emission radiation, the Berlage oscillator. The paper considers the Rosenbrock numerical method of the fourth order of accuracy, a parallel modification of a physically informed neural network into three subdomains (TriDomainPINN), as well as a neural network based on Legendre polynomials (LeNN). The parallel version of PINN makes it possible to increase the efficiency of the solution and reduce the learning time by decomposing the modeling area. All algorithms are implemented in Python using the PyTorch library; the implementation provides a mechanism for early stopping of network training and the distribution of collocation points according to Chebyshev’s law. Accuracy, convergence rate, and computational efficiency were evaluated for each method. Numerical experiments show that the Legendre polynomial network provides high approximation accuracy with a significant reduction in computational costs and time.
Key words: polynomial neural networks, PINN, MLP, LeNN, Berlage pulse, orthogonal polynomials, machine learning, signal approximation.
Sergienko D.F. Comparative analysis of neural network methods for solving the model of a single dislocation source of geoacoustic emission is licensed under a Creative Commons Attribution 4.0 International License.
Citation in English: Mathematical Physics and Computer Simulation. Vol. 29 No. 2 2026, pp. 53-71
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