Artificial Neural Networks

Luiz Biondi Neto, Francisco José da Cunha Pires Soeiro, Haroldo Fraga de Campos Velho (), José Demisio Simões da Silva, Ezzat Selim Chalhoub and Antônio José da Silva Neto
Additional contact information
Luiz Biondi Neto: Rio de Janeiro State University (UERJ)
Francisco José da Cunha Pires Soeiro: Rio de Janeiro State University (UERJ)
Haroldo Fraga de Campos Velho: National Institute for Space Research (INPE)
José Demisio Simões da Silva: National Institute for Space Research (INPE)
Ezzat Selim Chalhoub: National Institute for Space Research (INPE)
Antônio José da Silva Neto: Rio de Janeiro State University

Chapter Chapter 7 in Computational Intelligence Applied to Inverse Problems in Radiative Transfer, 2023, pp 51-65 from Springer

Abstract: Abstract In this chapter, the description of the method called Artificial Neural Networks (ANNs) is presented, including a brief history, the algorithm, and its application to the inverse radiative transfer problem, for the determination of the optical thickness, single scattering albedo, and diffuse reflectivities in the internal part of the boundary surfaces of one-dimensional homogeneous participating media. The results obtained with the combination of the ANNs with the Levenberg–Marquardt deterministic method (LM) are presented. Furthermore, it is also shown how to obtain estimates for the single scattering albedo and optical thickness in one-dimensional homogeneous participating media, employing ANNs trained with patterns generated with a Monte Carlo Method (MC), with different levels of precision.

Keywords: Artificial Neural Networks (ANNs); ANN Method Algorithm; Multilayer perceptron; Monte Carlo Method; Training; Supervised learning; Generalization; One-dimensional homogeneous participating medium; Radiative transfer; Levenberg–Marquardt method (search for similar items in EconPapers)
Date: 2023
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:978-3-031-43544-7_7

Ordering information: This item can be ordered from
http://www.springer.com/9783031435447

DOI: 10.1007/978-3-031-43544-7_7

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 ().