# Rapid Estimation of Earthquake Magnitude and Source Parameters Using Genetic Algorithms
###### Abstract  
To minimize the impacts of large losses and optimize the emergency response when a large earthquake occurs, an accurate early warning of an earthquake or tsunami is crucial. One important parameter that can provide an accurate early warning is the earthquake's magnitude. This study proposes a method for estimating the magnitude, and some of the source parameters, of an earthquake using genetic algorithms (GAs). In this study, GAs were used to perform an inversion of [PERSON]'s model from earthquake displacement data. In the first stage of the experiment, the GA was used to inverse the displacement calculated from the forward calculation in [PERSON]'s model. The best performance of the GA was obtained by tuning the hyperparameters to obtain the most functional configuration. In the second stage, the inversion method was tested on GPS time series data from the 2011 Tohoku Oki earthquake. The earthquake's displacement was first estimated from GPS time series data using a detection and estimation formula from previous research to calculate the permanent displacement value. The proposed method can estimate an earthquake's magnitude and four source parameters (i.e., length, width, rake, and slip) close to the real values with reasonable accuracy. m 2021 11 11852 11.11852 11. As a result, the earthquake's impacts were larger than expected and caused a greater loss of life and infrastructure. Conventionally, rapid magnitude estimation is still carried out based on seismometer data using magnitude scales that can be derived as soon as an earthquake occurs. Such scales include the body-wave magnitude (\(Mbw\)), surface-wave magnitude (\(Msw\)), and moment magnitude (\(Mw\)) measurement scales [1]. However, these types of measurements have significant limitations when estimating values due to saturation problems hampering measurement equipment used to record seismic signals, especially in the event of a large earthquake. The signal amplitude is often clipped during major earthquakes. Stations nearest to the epicenter are the most important sources of information to obtain an early estimation of an earthquake's magnitude. Unfortunately, these nearby stations are more susceptible to the saturation and clipping-off problems mentioned above, which can cause the magnitude to be underestimated compared with the actual value [4; 5; 7]. For example, in the 2004 Sumatran earthquake that triggered the most fatal tsunami in the country's history, an initial estimate of the earthquake's magnitude was released 11 min after the earthquake occurred: 8.0 using \(Mbw\)[1]. One hour after the earthquake occurred, the value was revised using \(Msw\) to 8.5. The next update was given five hours after the earthquake, and the newly estimated magnitude was 9.0 [1]. The actual magnitude of 9.2 was ultimately released a few days later. The initial estimated value of magnitude (8.0) resulted in the tsunami early warning decision being underestimated, which led to a suboptimal emergency response. In the three hours after the earthquake occurred, a huge tsunami crossed the sea at high speed and devastated the nearby area [5; 7]. When the Tohoku Oki earthquake occurred in 2011, the actual magnitude was similarly underestimated. This underestimation provided an inaccurate tsunami early warning followed by an emergency response that was far below the recommended standard. Three minutes after the earthquake occurred, the estimated magnitude released by the Japan Meteorology Agency was 7.9 [5]. This estimation was updated to 8.4 one hour and 20 min after the earthquake. A few days later, the actual magnitude was determined to be an \(Mw\) of 9.0. In the 25 min after the earthquake occurred, a large tsunami destroyed the coast nearest to the source of the earthquake [5; 7]. These two earthquake events show the importance of providing an accurate magnitude estimation within the crucial few minutes after the earthquake occurs [1; 2; 3; 4; 5; 7; 8].