Abstract

Estimation of fault plane parameters play an important role for determination of an earthquake occurance time. Complex nonlinear structure of the fault plane models make the estimation of fault plane parameters more challenging by using classical optimization methods. In this study, stochastic optimization methods, Nelder-Mead simplex (NMS), Simulated Annealing (SA), Genetic Algorithm (GA), and hybrid of GA and NMS (GAHNMS) are used to estimate the fault plane parameters. Simulated data set is used for the application of optimization algorithms. The results show that the GAHNMS is the most preferred method among the other stochastic optimization methods.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.