Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Silvio Pierini"'
Autor:
Nicola Lopane, Matteo Albéri, Alessio Barbagli, Enrico Chiarelli, Tommaso Colonna, Fabio Gallorini, Enrico Guastaldi, Fabio Mantovani, Dario Petrone, Silvio Pierini, Kassandra Giulia Cristina Raptis, Virginia Strati
Publikováno v:
Agronomy, Vol 14, Iss 11, p 2489 (2024)
Using a novel joint inversion approach, this study tackles the challenge of accurately characterizing subsurface electrical resistivity in vineyards, a critical and strategic aspect of precision viticulture. For the first time, we integrate 3D Galvan
Externí odkaz:
https://doaj.org/article/ef10db7281634898a13d300e51eaa985
Publikováno v:
Near Surface Geophysics. 18:205-215
In this work, we describe an experiment concerning global–local full‐waveform inversion, carried out on a P‐wave seismic reflection profile that was acquired at Luni, an archaeological site in Italy. The global full‐waveform inversion makes u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aef6d9d0bab073c3bc1b550bb456cd54
https://doi.org/10.1002/nsg.12096
https://doi.org/10.1002/nsg.12096
Publikováno v:
Near Surface Geophysics. 18:515-543
We compare two Monte Carlo inversions that aim to solve some of the main problems of dispersion curve inversion: deriving reliable uncertainty appraisals, determining the optimal model parameterization and avoiding entrapment in local minima of the m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::789ffc5afa8c4b2cd58335227f3f86cf
https://doi.org/10.1002/nsg.12100
https://doi.org/10.1002/nsg.12100
Publikováno v:
GEOPHYSICS. 84:R295-R310
Genetic algorithms (GAs) usually suffer from the so-called genetic-drift effect, which reduces the genetic variability within the evolving population making the algorithm converge toward a local minimum of the objective function. We have developed an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::204a198a62a4bf6be3489e1df04ecc0c
https://doi.org/10.1190/geo2018-0374.1
https://doi.org/10.1190/geo2018-0374.1
We have compared the performances of six recently developed global optimization algorithms: imperialist competitive algorithm, firefly algorithm (FA), water cycle algorithm (WCA), whale optimization algorithm (WOA), fireworks algorithm (FWA), and qua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54e550b1a6b8d31d8f8eeb77dde2d731
http://hdl.handle.net/11568/1015121
http://hdl.handle.net/11568/1015121
