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Meng S B，Zhao J W，Liu Z X. 2022. Prediction model of seismic amplification effect in sedimentary valley based on differential evolution-artificial neural network. Acta Seismologica Sinica，44（1）：170−181. DOI: 10.11939/jass.20210141
Citation: Meng S B，Zhao J W，Liu Z X. 2022. Prediction model of seismic amplification effect in sedimentary valley based on differential evolution-artificial neural network. Acta Seismologica Sinica，44（1）：170−181. DOI: 10.11939/jass.20210141
shu

Prediction model of seismic amplification effect in sedimentary valley based on differential evolution-artificial neural network

  • 1.

    Tianjin Key Laboratory of Structural Protection and Reinforcement，Tianjin 300384，China

  • 2.

    School of Civil Engineering，Tianjin Chengjian University，Tianjin 300384，China

  • 3.

    Tianjin Key Laboratory of Soft Soil Characteristics and Engineering Environment，Tianjin 300384，China

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  • Received Date: August 26, 2021
  • Revised Date: December 08, 2021
  • Available Online: February 16, 2022
  • Published Date: March 17, 2022
    Graphical Abstract
    • Abstract
  • Sedimentary valley has obvious amplification effect on ground motions, which has an increase on the engineering damage. However, the propagation mechanism of seismic wave in sedimentary valley is complex, resulting in high nonlinearity and high coupling of influences of incident wave and site parameters on seismic amplification effect. First, based on the boundary element method, the scattering of seismic waves by sedimentary valley is solved. Prediction models of seismic amplification effect of semicircular and V-shaped sedimentary valley are established, with incident wave conditions, material properties and valley shapes as characteristic parameters and the seismic amplification factor of sedimentary valley as target parameters, and the dataset is constructed; Second, the calculation accuracy and stability of artificial neural network （ANN） and its optimization algorithm, i.e., differential evolution, are compared, and the sensitivity of characteristic parameters is analyzed. The results show that the ANN can predict the amplification effect of sedimentary valley, and the accuracy and stability of differential evolution-ANN prediction model are significantly improved; The incident wave frequency is the main influence factor of the seismic amplification coefficient of sedimentary valley, and the density ratio of internal and external medium has little effect. The conclusions can provide references for more complex local site effect prediction and assessment.
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    • References (42)
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