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A Comparative Analysis of Three Computational-Intelligence Metaheuristic Methods for the Optimization of TDEM DataNARA Subscribed
We focus on the performances of three nature-inspired metaheuristic methods for the optimization of time-domain electromagnetic (TDEM) data: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO) and the Grey Wolf Optimizer (GWO) algorithms. While GA and PSO have been used in a plethora of geophysical applications, GWO has received little attention in the literature so far, despite promising outcomes. This study dir...
This study aimed to monitor the aerobic bioremediation of diesel oil-contaminated soil by measuring: a) the CO 2 production; 2) the fluorescein production; 3) the residual diesel oil concentration. Moreover, the complex dielectric permittivity was monitored through an open-ended coaxial cable. Several microcosms were prepared, changing the water content (u% = 8–15% by weight), the carbon to nitrogen ratio (C/N = 20–450), and t...
This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical fields are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a...
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