## 2 Inversion Analysis  
The conventional inversion method used in the present study is described in this section. Determination of the Starting Model Parameter (SMP), depth resolution analysis, layer sensitivity analysis, and final inversion analysis are the major steps in the inversion procedure, as shown in Figure 2 (on the right-hand side of the flow diagram). Firstly, the SMP was determined based on the theoretical dispersion curve and the assumption of the parameters. An assumption of the number of layers, as well as of each layer's thickness, was made for the iterative procedure [15]. Subsequently, depth resolution analysis and layer sensitivity analysis refined the starting model in the first step. Several iterations are required for the steps of refining the starting model. These three steps constitute the preliminary inversion analysis. After completing the preliminary inversion analysis, the final inversion analysis, which has been denoted as Inversion Engine in the flow diagram, can be performed. The starting model is called a preliminary shear wave velocity profile, since shear wave velocity is used as a model parameter for the inversion procedure. There are two steps involved in constructing the preliminary shear wave velocity profile. A preliminary shear wave velocity profile is determined as the first step. Based on the experimental dispersion data distribution, layer thicknesses and the number of layers are calculated for the preliminary profile. In the second step, another profile is determined from the preliminary profile based on the layering determined in the first step. The second profile is used for the inversion analysis. Figure 2: Flow diagram describing the conventional inversion procedure and how the ML algorithm would simplify the procedure. The measurement of depth resolution evaluates the optimum resolvable depth for a given experimental dispersion curve [24]. The deepest resolvable layer is dependent on the penetration depth or the zone stressed by the surface wave. The penetration depth is influenced by the frequencies generated by the source on the surface and the stiffness structure of the subsurface. Inversion analysis is very reliant on the layering of the starting model. Layering of the subsurface structure is assumed initially for the inversion technique. Consequently, a measure must be provided so as to indicate how good the assumed layering is. Layer sensitivity analysis decides whether or not the assumed layering is suitable. The assumed layering could be improved to provide a proper resolution, depending on the layer sensitivity analysis [24]. The inversion engine, as illustrated in Figure 2, represents the principal flow of the inversion analysis. This engine has two components: one calculates root mean square error (RMSE), and the other updates the model parameters. The parameters include shear wave velocity, Poisson's ratio, compression wave velocity, mass density, and the material damping ratio [28]. Wave velocities are updated for every iteration; however, the parameters, such as Poisson's ratio, mass density, and the material damping ratio, are reasonably assumed, since their effect on phase velocity is considerably small. Compression wave velocity is explicitly related to shear wave velocity and Poisson's ratio. Thus, it can be calculated using the assumed Poisson's ratio and the updated shear wave velocity. Therefore, only shear wave velocity was used as the modal parameter for the inversion analysis. The sensitivity matrix, G, and the change in a model parameter, \(\Delta m\), are determined to update the model parameters. After completing the preliminary inversion analysis, the final inversion analysis can be performed. Iteration of the inversion analysis is continued until the theoretical dispersion curve is similar enough to the experimental dispersion curve [29]. RMSE\({}_{5}\) measures the misfit between the theoretical curve and the experimental dispersion curve and evaluates the goodness of the shear wave velocity profile.