# Predicting Models for Local Sedimentary Basin Effect Using a Convolutional Neural Network
## 1 Introduction  
As the propagation medium of seismic waves and the ground of building structures, a local site will significantly affect the ground motion. Previous investigations have recorded relatively serious earthquake damages in a basin, which is a special site, and its influence on ground motion has been studied. The basin effect includes the selective amplificationof long-period ground motion by the soft soil layer and the abnormal amplification of the basin edge [1; 2]. These special amplifying characteristics of ground motion are some of the representative parameters to measure the ground motion amplification of the basin, as well as the amplification of the peak of the ground acceleration. Therefore, it is of great importance to predict the peak amplification and location of the ground motion acceleration in the basin to evaluate the safety of many high-rise buildings located in basins in inner cities. The influence analysis of sedimentary basins on ground motion is theoretically a problem of two-dimensional (2D) or three-dimensional (3D) dynamic response analysis. More efficient and flexible numerical simulation methods are mostly adopted, and detailed site data are needed to establish a more accurate 3D computational model. With the development of computing technology, numerical methods have overcome the challenge of computational accuracy and stability, and have achieved great development and wide application. In terms of computing software, general commercial finite element software is widely used in the field of research and design currently, including ANSYS, ABAQUS, FLAC, LS-DYNA, ADINA, Marc, etc. [3], all of which have perfect modeling, solving, and post-processing functions. In view of the physical characteristics of basins, many scholars have improved the level of existing special analysis methods from many aspects and perspectives, and have developed a series of special analysis software, such as CESAR-LCPC [4] and AHNSE [5]. Based on the current analysis techniques, complex 2D and 3D computational models reflecting as many factors as possible have been established to reflect the detailed characteristics of the sedimentary basin geological structure and focal information, etc., and different numerical methods are used to reproduce the ground motion characteristics. [PERSON] et al. [6] conducted extensive numerical analysis on the linear viscoelastic response of homogeneous sedimentary basins and explored the potential additional influence of sediment heterogeneity and nonlinearity on the weighting coefficient through a finite element model developed in ABAQUS. [PERSON] et al. [7] used the scaled boundary finite element method to directly deal with irregular phenomena in the time domain, and discuss the scattering and amplification of seismic waves under topographic and geological conditions. [PERSON] et al. [8] reconstructed the engineering geological model of the alluvial valley and evaluated the local response of the ground motion in terms of surface propagation, amplification function, and cumulative kinetic energy by using a 2D finite element numerical simulation method. The basin effect is often caused by the combined action of many factors, such as subsurface media and irregular site geometries. The 2D characteristics of the variation of heterogeneous media in the basin have been proven to change the nature of seismic wave propagation from deep underground to the surface. The results show that for sedimentary basins with significant amplification characteristics, it is necessary to reflect the joint influence of the spatial geometric characteristics and the physical characteristics of the sedimentary soil layer. Therefore, on the basis of qualitative research, how to quantitatively analyze the amplification effect of different factors on the basin, how to reasonably evaluate the basin effect, and how to scientifically predict the ground motion are the key problems to be solved in engineering applications.