Abstract—Inversion is a critical and challenging task in geophysical research. Geophysical inversion can be formulated as an optimization problem to find the best parameters whose forward synthesis data most fit the observed data. The inverse problems are usually highly non-linear, multi-modal as well as ill-posed, so conventional optimization algorithms cannot handle it very efficiently. In the past decades, genetic algorithm (GA) and its many variants are widely applied to inverse problems and achieve great success. Swarm intelligence algorithms are a family of global optimizers inspired by swarm phenomena in nature, and have shown better performance than GA for diverse optimization problems. However, swarm intelligence algorithms are not...
The joint inversion of multiple data sets encompasses the advantages of different geophysical metho...
Genetic algorithms use the survival of the fittest analogy from evolution theory to make random walk...
In this paper, an implementation of Backtracking search optimization (BSA), a non-gradient iterative...
Inversion is a critical and challenging task in geophysical research. Geophysical inversion can be f...
We have compared the performances of six recently developed global optimization algorithms: imperial...
A geophysical inverse problem consists in obtaining the earth model for which the predicted data bes...
We compare the performances of four different stochastic optimisation methods using four analytic ob...
Genetic algorithms (GAs), global optimization methods that mimic Darwinian evolution are well suited...
This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform sto...
Interpreting geophysical data requires solving nonlinear optimization problem(s) in inversion. Ana...
The solution of non-linear geophysical inverse problems presents several challenges mainly related t...
This PhD work focuses on introducing big data analytics methodologies to the exploration geophysics ...
We use Legendre polynomials to reparametrize geophysical inversions solved through a particle swarm ...
We describe a new genetic-algorithm (GA) inversion technique and apply it to a vertical seismic prof...
In this study, four metaheuristic algorithms including particle swarm optimization (PSO), genetic al...
The joint inversion of multiple data sets encompasses the advantages of different geophysical metho...
Genetic algorithms use the survival of the fittest analogy from evolution theory to make random walk...
In this paper, an implementation of Backtracking search optimization (BSA), a non-gradient iterative...
Inversion is a critical and challenging task in geophysical research. Geophysical inversion can be f...
We have compared the performances of six recently developed global optimization algorithms: imperial...
A geophysical inverse problem consists in obtaining the earth model for which the predicted data bes...
We compare the performances of four different stochastic optimisation methods using four analytic ob...
Genetic algorithms (GAs), global optimization methods that mimic Darwinian evolution are well suited...
This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform sto...
Interpreting geophysical data requires solving nonlinear optimization problem(s) in inversion. Ana...
The solution of non-linear geophysical inverse problems presents several challenges mainly related t...
This PhD work focuses on introducing big data analytics methodologies to the exploration geophysics ...
We use Legendre polynomials to reparametrize geophysical inversions solved through a particle swarm ...
We describe a new genetic-algorithm (GA) inversion technique and apply it to a vertical seismic prof...
In this study, four metaheuristic algorithms including particle swarm optimization (PSO), genetic al...
The joint inversion of multiple data sets encompasses the advantages of different geophysical metho...
Genetic algorithms use the survival of the fittest analogy from evolution theory to make random walk...
In this paper, an implementation of Backtracking search optimization (BSA), a non-gradient iterative...