Multi-Particle Collision Algorithm for Solving an Inverse Radiative Problem
R. Hernández Torres (),
E. F. P. Luz () and
H. F. Campos Velho ()
Additional contact information
R. Hernández Torres: National Institute for Space Research (INPE)
E. F. P. Luz: National Institute for Space Research (INPE)
H. F. Campos Velho: National Institute for Space Research (INPE)
Chapter Chapter 26 in Integral Methods in Science and Engineering, 2015, pp 309-319 from Springer
Abstract:
Abstract An inverse radiative transfer problem formulated as a finite dimensional optimization problem, using Multi-Particle Collision Algorithm with a pre-regularization strategy. The radiation propagation in a finite space domain, under isotropic-scattering, assuming plane-parallel geometry is considered. The optical properties, absorption and scattering coefficients, have space dependency. The problem is described by linear Boltzmann equation, considering polar angle discretization and azimuthal symmetry. The forward problem is solved using the discrete ordinates. The inverse problem, reconstruction of the albedo profile, is performed minimizing the square difference between measured radiance and the photon concentration computed from the mathematical forward model emerging from the body. A large number of particles is generated, and those smoother particles are selected. This scheme is called intrinsic regularization. Multi-Particle Collision Algorithm is a stochastic method for global optimization, also called meta-heuristic, and is used to solve the inverse problem. Noiseless and noisy data of the emergent radiation intensities were employed to compute the albedo profile. Good inverse solutions are obtained with the proposed approach.
Keywords: Inverse radiative problem; Pre-regularization; Intrinsic regularization; Meta-heuristic algorithm; Multi-Particle Collision Algorithm (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-16727-5_26
Ordering information: This item can be ordered from
http://www.springer.com/9783319167275
DOI: 10.1007/978-3-319-16727-5_26
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().