Inverse Modeling Problems in Task Enrichment for STEM Courses

2020 ◽  
Author(s):  
Victor Martinez-Luaces ◽  
José Antonio Fernández-Plaza ◽  
Luis Rico
Keyword(s):  
Inverse Modeling

Obtaining the Spatial Distribution of Water Content along a TDR Probe Using the SCEM-UA Bayesian Inverse Modeling Scheme

2004 ◽  
Vol 3 (4) ◽  
pp. 1128-1145 ◽  
Author(s):  
Timo J. Heimovaara ◽  
Johan A. Huisman ◽  
Jasper A. Vrugt ◽  
Willem Bouten
Keyword(s):  
Spatial Distribution ◽  
Water Content ◽  
Inverse Modeling

Multiphase Inverse Modeling: Review and iTOUGH2 Applications

2004 ◽  
Vol 3 (3) ◽  
pp. 747-762 ◽  
Author(s):  
Stefan Finsterle
Keyword(s):  
Inverse Modeling

Estimating Regional Methane Emissions Through Atmospheric Measurements and Inverse Modeling.

2019 ◽  
Author(s):  
Cosmin Safta ◽  
Ray Bambha ◽  
Hope Michelsen
Keyword(s):  
Inverse Modeling ◽  
Methane Emissions ◽  
Atmospheric Measurements

scholarly journals Fluvial inverse modeling for inferring the timing of Quaternary uplift in the Simbruini range (Central Apennines, Italy)

2021 ◽  
Author(s):  
Michele Delchiaro ◽  
Veronica Fioramonti ◽  
Marta Della Seta ◽  
Gian Paolo Cavinato ◽  
Massimo Mattei
Keyword(s):  
Inverse Modeling ◽  
Central Apennines

scholarly journals A Review of Geophysical Modeling Based on Particle Swarm Optimization

2021 ◽  
Author(s):  
Francesca Pace ◽  
Alessandro Santilano ◽  
Alberto Godio
Keyword(s):  
Particle Swarm Optimization ◽  
Inverse Modeling ◽  
Critical Evaluation ◽  
Particle Swarm ◽  
Geophysical Data ◽  
Magnetic Data ◽  
Data Sets ◽  
Swarm Optimization ◽  
Geophysical Modeling ◽  
Original Works

AbstractThis 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 critical evaluation of their benefits and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle different data sets without conflicting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the benefit of PSO practitioners or inexperienced researchers.

Estimation of Lung Properties Using ANN-Based Inverse Modeling of Spirometric Data

2019 ◽  
pp. 561-572 ◽  
Author(s):  
Adam G. Polak ◽  
Dariusz Wysoczański ◽  
Janusz Mroczka
Keyword(s):  
Inverse Modeling

scholarly journals Emission factor estimation of ca. 160 emerging organic microcontaminants by inverse modeling in a Mediterranean river basin (Llobregat, NE Spain)

2015 ◽  
Vol 520 ◽  
pp. 241-252 ◽  
Author(s):  
Zoran Banjac ◽  
Antoni Ginebreda ◽  
Maja Kuzmanovic ◽  
Rafael Marcé ◽  
Martí Nadal ◽  
...  
Keyword(s):  
River Basin ◽  
Inverse Modeling ◽  
Emission Factor ◽  
Mediterranean River ◽  
Ne Spain ◽  
Factor Estimation

Estimation of Landfill Gas Generation Rate and Gas Permeability Field of Refuse Using Inverse Modeling

2010 ◽  
Vol 90 (1) ◽  
pp. 41-58 ◽  
Author(s):  
Yoojin Jung ◽  
Paul Imhoff ◽  
Stefan Finsterle
Keyword(s):  
Inverse Modeling ◽  
Gas Permeability ◽  
Landfill Gas ◽  
Generation Rate ◽  
Gas Generation ◽  
Gas Generation Rate ◽  
Permeability Field
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