## 1 Introduction
Moreover, it is sensitive to noisy signals [26]. On the other hand, the EMD method is an adaptive scheme, which is designed to process nonlinear and non-stationary signals according to the frequencies contented in the time-series signal. Its utilization, however, is limited in the MPI because of the so-called mode mixing effect, which is the assignment of more than one frequency to each frequency band, limiting the accurate estimation of the modal parameters [27]. Although different improvements to the EMD method have been proposed to mitigate this effect [27; 28], the developed techniques still have problems when they deal with noisy signals. From this point of view, other signal processing techniques should be explored in order to perform the MPI in an accurate and reliable way. MPI of real-life structures, especially large ones, is complicated; in fact, a single computational technique may not be sufficient. The works developed by [28; 29; 30; 31] show that the utilization of multi-paradigm approaches can lead to develop methodologies capable of dealing with noisy signals, as well as to improve accuracy, efficiency, and stability of the resulting algorithm. Recently, a methodology based on the utilization of the synchrosqueezed wavelet transform (SWT) in combination with Hilbert transform (HT), and Kalman Filter (FK) is proposed for MPI [11]. The work proposed in that article uses SWT to decompose the signal into its individual modes; then; for each mode, and it is applied HT to obtain its instantaneous amplitude, which is used to estimate both the natural frequency and damping ratio. It should be pointed out that the methodology has to make use of KF in order to smooth the obtained instantaneous amplitude since any imperfection in this signal could potentially cause a miscalculation of these values. KF requires setting different parameters to obtain the best possible result, making necessary to design a procedure to find out these values, which change depending on the nature of the sensors used to acquire the signal. Evidently, sometimes they can be difficult to reach in a practical way, thus deteriorating the accuracy and reliability of the modal parameters value. For these reasons, it should be desirable to develop a new methodology that does not require designing calibration procedures to ensure the best possible result, and also to improve the accuracy of the modal parameters values. In particular, as the damping ratios usually have a very small value, the accurate estimation of the damping ratio is a complicated issue [32]. In the literature, many problems that involve the search and selection of the best-suited parameters for specific models have been solved by means of optimization algorithms, where genetic algorithms (GA) have demonstrated to be an efficient tool for solving these problems [33]. Taking advantages of the multi-paradigm approaches, this paper proposes a new methodology based on the utilization of the SWT fused with GA to identify natural frequencies and damping ratios of civil structures. In general, it uses two steps to estimate the modal parameters of civil structures. In Step 1, the mode extraction is performed by using the NExT and SWT algorithms, where NExT converts the measured response into a free-decay one and SWT decomposes the converted signal into its fundamental components. In Step 2, the natural frequencies and damping ratios of every mode are calculated using a GA-based approach, where a fusion of novel objective functions for the estimation of natural frequencies and damping ratios is proposed. It is worth noting that the appropriate selection of the search space and the utilization of the micropopulation concept will reduce the required time to estimate the optimal solution, allowing its obtaining in a practical way. In order to validate the efficacy and performance of the proposed methodology, two study cases are carried out.