2022
DOI: 10.1080/23311916.2021.2003522
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Numerical simulation of inverse geochemistry problems by regularizing algorithms

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Cited by 5 publications
(3 citation statements)
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“…There are many methods of global minimization, each of which has its advantages and limitations. Some of the most common methods include evolutionary algorithms, genetic algorithms, particle swarm methods, annealing simulation optimization methods, and more [32][33][34][35]. And when the objective function is nonlinear and undifferentiable, direct search methods are preferred.…”
Section: The Methods Of Differential Evolutionmentioning
confidence: 99%
“…There are many methods of global minimization, each of which has its advantages and limitations. Some of the most common methods include evolutionary algorithms, genetic algorithms, particle swarm methods, annealing simulation optimization methods, and more [32][33][34][35]. And when the objective function is nonlinear and undifferentiable, direct search methods are preferred.…”
Section: The Methods Of Differential Evolutionmentioning
confidence: 99%
“…Also, based on the data obtained using remote sensing, another inverse problem related to magnetotelluric sounding (MTS) is considered [17], [18]. The general approach to the inverse problems of MTS is to reconstruct the physical characteristics of the earth's crust based on data on physical fields measured on the Earth's surface.…”
Section: Introductionmentioning
confidence: 99%
“…Usually, to cope with such difficulties, reformulation of the tasks is used. These inverse problems in the field of magnetotelluric sensing, as a rule, are nonlinear and have several possible solutions [17], [18]. To solve them, geophysicists often use regularization methods, including linearized approaches [19]- [27].…”
Section: Introductionmentioning
confidence: 99%