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Artificial Neural Networks

In: Computational Intelligence Applied to Inverse Problems in Radiative Transfer

Author

Listed:
  • 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)

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.

Suggested Citation

  • Luiz Biondi Neto & Francisco José da Cunha Pires Soeiro & Haroldo Fraga de Campos Velho & José Demisio Simões da Silva & Ezzat Selim Chalhoub & Antônio José da Silva Neto, 2023. "Artificial Neural Networks," Springer Books, in: Antônio José da Silva Neto & José Carlos Becceneri & Haroldo Fraga de Campos Velho (ed.), Computational Intelligence Applied to Inverse Problems in Radiative Transfer, chapter 0, pages 51-65, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-43544-7_7
    DOI: 10.1007/978-3-031-43544-7_7
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