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Regional Attenuation Relationships: Regression vs Neural Network Analysis

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International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019 (EMMFT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1259))

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Abstract

Neural networks are applied now in many fields. It is de facto efficient and flexible tool for analysis, which could be applied where other traditional approaches are impossible. It also gives new knowledge on the basis of data analysis. In this paper, traditional regression approach is considered in comparison with neural network for regional attenuation model assessment - peak ground acceleration (PGA) variation with magnitude and hypocentral distance. Such a simple set of parameters is not usual for neural networks, but simple, and result differences are clear. Dataset was prepared on the base of K-net network data. Records of stations with Vs 30 > 700 m/s were used. Accelerations have wide dispersion, and both of the approaches gave different results: when regression is forced by a given form of linear combination, neural network is more flexible. For example, it was found that for magnitude M = 4, in close distances R > 10 km PGA(R) curve is close to M < 4 curves, and for R > 10 km has the same manner as M > 4 curves. So M = 4, R = 10 km is some kind of “point of inflection” between near field and far field zones.

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Authors and Affiliations

  1. Geophysical Institute of Vladikavkaz Scientific Center, Markov Street, 93a, 362002, Vladikavkaz, Russia

    Vladislav Zaalishvili & Dmitry Melkov

  2. North Ossetian State University after K. L. Khetagurov, Vatutina 44-46, 362025, Vladikavkaz, North Ossetia - Alania, Russia

    Vladislav Zaalishvili & Dmitry Melkov

Authors
  1. Vladislav Zaalishvili
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  2. Dmitry Melkov
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Correspondence to Vladislav Zaalishvili .

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Editors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic, Saint Petersburg, Russia

    Vera Murgul

  2. Saint Petersburg State University of Architecture and Civil Engineering, Saint Petersburg, Russia

    Viktor Pukhkal

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Zaalishvili, V., Melkov, D. (2021). Regional Attenuation Relationships: Regression vs Neural Network Analysis. In: Murgul, V., Pukhkal, V. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2019. EMMFT 2019. Advances in Intelligent Systems and Computing, vol 1259. Springer, Cham. https://doi.org/10.1007/978-3-030-57453-6_7

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