@InCollection{TorresLuzCamp:2015:MuCoAl,
author = "Torres, Reynier Hernandez and Luz, Eduardo F{\'a}vero Pacheco da
and Campos Velho, Haroldo Fraga de",
title = "Multi-Particle Collision Algorithm for Solving an Inverse
Radiative Problem",
booktitle = "Integral Methods in Science and Engineering: Theoretical and
Computational Advances",
publisher = "Birkh{\"a}use",
year = "2015",
editor = "Constanda, C. and Kirsch, A.",
pages = "309--319",
address = "New York (USA)",
keywords = "Radiative transfer, Inverse problem, Albedo identification, MPCA:
multi-particle collision algorithm.",
abstract = "An inverse radiative transfer problem formulated as a finite
dimensionaloptimization 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
prop-erties, absorption and scattering coefficients, have space
dependency. Theproblem is described by linear Boltzmann equation,
considering polar anglediscretization and azimuthal symmetry. The
forward problem is solved us-ing the discrete ordinates. The
inverse problem, reconstruction of the albedoprofile, is performed
minimizing the square difference between measured radi-ance and
the photon concentration computed from the mathematical
forwardmodel emerging from the body.A large number of particles is
generated, and those smoother particles areselected. This scheme
is called intrinsic regularization.Multi-Particle Collision
Algorithm is a stochastic method for global op-timization, also
called metaheuristic, and it is codified into
multiprocessingmachine. The parallel processing reduces the
computation time, since multi-ples particles are evaluated at the
same time. Noiseless and noisy data of theemergent radiation
intensities were employed to compute the albedo profile.Good
inverse solutions are obtained with the proposed approach.1.2
IntroductionOptimization is the area of the Applied Mathematics
that studies the theoryand techniques to finding the best
available values to optimize (minimize ormaximize) some objective
function, also called error function or cost function.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and
{Instituto Nacional de Pesquisas Espaciais (INPE)}",
isbn = "9783319167268",
label = "lattes: 5142426481528206 3 TorresLuzCamp:2015:MuCoAl",
language = "en",
targetfile = "1_torres.pdf",
url = "http://www.springer.com/us/book/9783319167268",
urlaccessdate = "02 maio 2024"
}