## 4 Methods and Materials  
In the SASW method, Rayleigh waves are generated by any impact source and detected by two receivers before then being recorded by a spectrum analyzer, as shown in Figure 8. Rayleigh wave data were collected and transformed into the frequency domain through the use of a dynamic signal analyzer [44]. The seismic experiments (SASW) were carried out at 50 different locations in Penin-sular Malaysia. SASW data are from a broad collection of geological and geotechnical site conditions ranging from recent alluvium, granitic to metasedimentary formations with geotechnical consistency of soft/loose to hard/dense soil conditions. The dispersion curves of all 50 corresponding sites can be found in the appendices. During the tests, both geophones were placed 0.5 m away from the specific points so as to maintain a 1 m distance between said geophones. Figure 7: K-fold cross-validation with k dataset. A rubber hammer, a geological hammer, a sledgehammer and a 10 kg weight were used to hit the soil surface in order to produce a transient vertical impact. Sources were placed at 1, 2, 4, 8, and 10 m from the first geophone, as shown in Figure 9. Thereafter, the data obtained from the field were analyzed using WinSASW 3.2.12. The depth was taken up to 6 m in dataset preparation for ML algorithm training and testing. The range of wavelengths of the dispersion curve needs to include the wavelengths for sampling shallow material and be long enough to penetrate deep layers. One source and receiver's setup are not sufficient to determine phase velocities over a wide range of wavelengths, which is required to evaluate a soil site with a depth of, for example, 30 ft (9 m) to 60 ft (18.3 m). Therefore, several measurement setups comprising different receiver spacings are used for this purpose. Figure 10 illustrates the summary of the SASW data analysis and the implementation of the ML through the use of the SASW method. The first task in analyzing the field measurements is the construction of an experimental dispersion curve. It is important to unwrap the phase spectrum in order to accomplish this task. An interpretation of the phase spectrum is required so as to unwrap the phase spectrum. The technique is called masking for interpreting the phase spectrum. The unwrapped phase spectrum and the receiver spacing determine the experimental dispersion curve by means of Equation (10):  
\[V_{PH}=f.\ \lambda\]  
\[V_{PH}=f.\ \frac{d}{\varphi/360^{\circ}} \tag{10}\]  
Figure 8: SASW method. Figure 9: Configuration of equipment for SASW test. where \(\varphi\) is the phase difference between the two receivers for the wave traveling with the frequency of \(f\), and \(d\) is the distance between the two receivers. The material properties and thickness of the soil profiles were assumed to obtain the theoretical dispersion curve. The soil layers were assumed to comprise 12 layers of 0.5 m thickness, a bulk density of 1800 kg m\({}^{-3}\), a Poisson's ratio of 0.3333, and a damping ratio of 0.02. The theoretical dispersion curve was generated based on this assumed parameter. Thereafter, the theoretical dispersion curve and the experimental dispersion curve obtained from the field were compared. The triangular part of Figure 10 is explained in detail in Figure 11. The parameters considered in the development of the ML were the shear wave velocity (\(V_{\mathrm{S}}\)), thickness, wavelength, and phase velocity of each layer. The theoretical dispersion curves from 50 tests were taken as input. A total number of 4782 data points was found from the 50 dispersion curves. Subsequently, all of the measurements obtained from the dispersion curve were divided into 12 layers of 6 m depth at a 0.5 m interval, as shown in Figure 11. The wavelengths were converted to an equivalent depth of \(\frac{1}{3}\lambda_{R}\).