MLP-NN vs Gauss-Newton files

Jamil, Ahsan

doi:10.6084/m9.figshare.24328972.v1

Title: MLP-NN vs Gauss-Newton files

Dataset
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Abstract

-Input files for randomly selected subset data (30 instances) from primary dipole-dipole forward modeling data.-Inversion results in surfer grid format as well as in .DAT format.-Scatterplots for MLP-NN vs Gauss-Newton present in the excel sheet.

Authors:

Jamil, Ahsan

New Mexico State Univ., Las Cruces, NM (United States); New Mexico State Univ., Las Cruces, NM (United States)

Publication Date:: Wed Oct 18 00:00:00 EDT 2023

DOE Contract Number:: SC0023132

Research Org.:: New Mexico State University, Las Cruces, NM (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Subject:: 58 GEOSCIENCES; Boosting; Electrical resistivity; Geophysics; Machine learning; Neural networks; Random forests

OSTI Identifier:: 2520487

DOI:: https://doi.org/10.6084/m9.figshare.24328972.v1

Citation Formats


                    Jamil, Ahsan. MLP-NN vs Gauss-Newton files.  United States: N. p., 2023. 
        Web.  doi:10.6084/m9.figshare.24328972.v1.

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                    Jamil, Ahsan. MLP-NN vs Gauss-Newton files.  United States.  doi:https://doi.org/10.6084/m9.figshare.24328972.v1

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                    Jamil, Ahsan. 2023.  
"MLP-NN vs Gauss-Newton files".  United States.  doi:https://doi.org/10.6084/m9.figshare.24328972.v1.  https://www.osti.gov/servlets/purl/2520487. Pub date:Wed Oct 18 00:00:00 EDT 2023

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@article{osti_2520487,

  title        = {MLP-NN vs Gauss-Newton files},

  author       = {Jamil, Ahsan},

  abstractNote = {-Input files for randomly selected subset data (30 instances) from primary dipole-dipole forward modeling data.-Inversion results in surfer grid format as well as in .DAT format.-Scatterplots for MLP-NN vs Gauss-Newton present in the excel sheet.},

  doi          = {10.6084/m9.figshare.24328972.v1},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Oct 18 00:00:00 EDT 2023},

  month        = {Wed Oct 18 00:00:00 EDT 2023}

}

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DOI: https://doi.org/10.6084/m9.figshare.24328972.v1

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