Estimation of Fault Plane Parameters by Using Stochastic Optimization Methods

Özlem Türkşen(1*)

(1) Ankara University, Faculty of Science, Statistics Department, Turkey
(*) Corresponding author

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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.
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Fault Plane Parameters; Nelder-Mead Simplex (NMS); Simulated Annealing (SA); Genetic Algorithm (GA); Hybrid of GA and NMS (GAHNMS)

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