Optimizing Weibull Distribution Parameters for Improved Earthquake Modeling in Japan: A Comparative Approach

Abstract

The Weibull distribution is considered one of the important distributions used in reliability and in the distribution of survival times and in neutrosophic prediction. This paper contained an estimate of a two-parameter Weibull distribution using three estimation methods. One of these methods for estimating parameters is the traditional method, which represents the estimation of the greatest possibility, and the other two methods are estimation using the sine algorithm. and cosine (SCA) and the Ant Colony Algorithm (ACO). The simulation method was used to compare the methods, and it was found that the best method for estimating the parameters of the Weibull distribution is the sine and cosine algorithm (SCA) method. Then, real data was used, represented by the intensity of the earthquake in Japan (Richter) for the period July 1, 2023, to July 16, 2023, to estimate the rate of earthquake intensity in Japan, since Japan is one of the countries most exposed to earthquakes, and it was shown from The results are that the average magnitude of the earthquake in Japan in the period studied is 3.328593, which can be said. Weak buildings may be greatly damaged, but strong buildings are not greatly damaged. Also, a neutrosophic simulation of the same set of data will be suggested for future applications.