2019
DOI: 10.3906/yer-1905-3
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Parameter Estimations from Gravity and Magnetic Anomalies Due to Deep-Seated Faults: Differential Evolution versus Particle Swarm Optimization

Abstract: Introduction Due to the mathematical nature of the gravity and magnetic methods in geophysics, numerous data processing techniques are easily performed to analyze their anomalies obtained from different types of investigations changing in a wide range of varieties. Based on the objectives of the investigations, the most commonly used techniques are generally separated into two different groups. The first group techniques, involving linear transformations, directional derivative-based techniques, image enhancem… Show more

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Cited by 17 publications
(15 citation statements)
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“…The length of the profile is 40 km, which was digitized at 1 km intervals from Radhakrishna Murthy et al (2001). Table 9 shows a brief comparison for the evaluation of this anomaly considering the results with the imBSA application in the present study and other solutions from previous studies using other metaheuristics such as DE and PSO (Ekinci et al, 2019), WOA (Gobashy et al, 2020), GPA (Di Maio et al, 2020) and SA (Biswas & Rao, 2021). From the table, it is seen that the common parameters attempted to be estimated are z1 and z2 for the metaheuristics considered.…”
Section: Perth Basin Magnetic Anomaly Australiamentioning
confidence: 99%
“…The length of the profile is 40 km, which was digitized at 1 km intervals from Radhakrishna Murthy et al (2001). Table 9 shows a brief comparison for the evaluation of this anomaly considering the results with the imBSA application in the present study and other solutions from previous studies using other metaheuristics such as DE and PSO (Ekinci et al, 2019), WOA (Gobashy et al, 2020), GPA (Di Maio et al, 2020) and SA (Biswas & Rao, 2021). From the table, it is seen that the common parameters attempted to be estimated are z1 and z2 for the metaheuristics considered.…”
Section: Perth Basin Magnetic Anomaly Australiamentioning
confidence: 99%
“…They showed the efficiency of magnetic anisotropy by solving magnetic data with inverse solution (Liu et al 2018). They modeled the gravity and magnetic anomaly of fault-shaped structures using Differential Evolution versus Particle Swarm Optimization method (Ekinci et al 2019).…”
Section: International Journal Of Scientific Advances Issn: 2708-7972mentioning
confidence: 99%
“…Among these methods, inversion methodologies are the frequently used data processing tool in anomaly interpretation. However, because of the well‐known ill‐posedness and non‐uniqueness nature of the geomagnetic data inversion problem, explanation of anomaly sources, that is, model parameter estimations, necessitate some special strategies and efficient approaches (Ekinci et al., 2019). Over the recent years, instead of derivative‐based local optimizers, derivative‐free nature‐inspired global optimizers and metaheuristics such as Particle Swarm Optimization (PSO) (Essa, Abo‐Ezz, et al., 2022; Essa & Elhussein, 2020; Fernández‐Martínez et al., 2010; Pallero et al., 2015; Roy et al., 2022; Santos, 2010), Very Fast Simulated Annealing (VFSA) (Biswas, 2016; Biswas & Acharya, 2016; Biswas & Rao, 2021), Ant Colony Optimization (Liu et al., 2014, 2015; Srivastava et al., 2014); Gray Wolf Optimizer (Agarwal et al., 2018; Chandra et al., 2017), Genetic‐Price Algorithm (Di Maio et al., 2020), Cuckoo Search Algorithm (Turan‐Karaoğlan & Göktürkler, 2021), Differential Search Algorithm (Alkan & Balkaya, 2018; A. Balkaya & Kaftan, 2021; Özyalın & Sındırgı, 2023), Bat Algorithm (Essa & Diab, 2022; Gobashy et al., 2021), Differential Evolution Algorithm (Ç. Balkaya, 2013; Du et al., 2021; Ekinci, Balkaya, & Göktürkler, 2020; Ekinci et al., 2023; Göktürkler et al., 2016; Hosseinzadeh et al., 2023; Roy et al., 2021a; Sungkono, 2020); Backtracking Search Algorithm (Ekinci, Balkaya, & Göktürkler, 2021), Manta‐Ray Foraging Optimization and Social Spider Optimization (Ben et al., 2022a, 2022b, 2022c), Barnacles Mating Optimization (BMO) (Ai et al., 2022) have gained increasing attention in geophysical inversion applications.…”
Section: Introductionmentioning
confidence: 99%
“…Among these methods, inversion methodologies are the frequently used data processing tool in anomaly interpretation. However, because of the well-known ill-posedness and non-uniqueness nature of the geomagnetic data inversion problem, explanation of anomaly sources, that is, model parameter estimations, necessitate some special strategies and efficient approaches (Ekinci et al, 2019). Over the recent years, instead of derivative-based local optimizers, derivative-free nature-inspired global optimizers and metaheuristics such as Particle Swarm Optimization (PSO) (Essa, Abo-Ezz, et al, 2022;Essa & Elhussein, 2020;Fernández-Martínez et al, 2010;Pallero et al, 2015;Roy et al, 2022;Santos, 2010), Very Fast Simulated Annealing (VFSA) (Biswas, 2016;Biswas & Acharya, 2016;Biswas & Rao, 2021), Ant Colony Optimization (Liu et al, 2014(Liu et al, , 2015Srivastava et al, 2014); Gray Wolf Optimizer (Agarwal et al, 2018;Chandra et al, 2017), Genetic-Price Algorithm (Di Maio et al, 2020), Cuckoo Search Algorithm (Turan-Karaoğlan & Göktürkler, 2021), Differential Search Algorithm (Alkan & Balkaya, 2018;A.…”
mentioning
confidence: 99%