Cargando…
Particle Swarm Optimization and Uncertainty Assessment in Inverse Problems
Most inverse problems in the industry (and particularly in geophysical exploration) are highly underdetermined because the number of model parameters too high to achieve accurate data predictions and because the sampling of the data space is scarce and incomplete; it is always affected by different...
Autores principales: | Pallero, José L. G., Fernández-Muñiz, María Zulima, Cernea, Ana, Álvarez-Machancoses, Óscar, Pedruelo-González, Luis Mariano, Bonvalot, Sylvain, Fernández-Martínez, Juan Luis |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512660/ https://www.ncbi.nlm.nih.gov/pubmed/33265187 http://dx.doi.org/10.3390/e20020096 |
Ejemplares similares
-
Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer
por: Cernea, Ana, et al.
Publicado: (2020) -
Predictive Mathematical Models of the Short-Term and Long-Term Growth of the COVID-19 Pandemic
por: Fernández-Martínez, Juan Luis, et al.
Publicado: (2021) -
Predictive mathematical models of the growth of the COVID-19 pandemic
por: Luis Fernández-Martínez, Juan, et al.
Publicado: (2022) -
Comparison of three mathematical models for COVID-19 prediction
por: Fernandez, Pelayo Martınez, et al.
Publicado: (2023) -
Gravity inversion of a fault by Particle swarm optimization (PSO)
por: Toushmalani, Reza
Publicado: (2013)