Programs and Code for Geothermal Exploration Artificial Intelligence

Moraga, Jim

doi:10.15121/1787330

Title: Programs and Code for Geothermal Exploration Artificial Intelligence

Dataset
Other Related Research

Abstract

The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including: - Land Surface Temperature K-Means classifier - Labeling AI using Self Organizing Maps (SOM) - Post-processing for Permanent Scatterer InSAR (PSInSAR) analysis with SOM - Mineral marker summarizing - Artificial Intelligence (AI) Data splitting: creates data set from a single raster file - Artificial Intelligence Model: creates AI from a single data set, after splitting in Train, Validation and Test subsets - AI Mapper: creates a classification map based on a raster file

Authors:

Moraga, Jim

Colorado School of Mines

Publication Date:: Tue Apr 27 00:00:00 EDT 2021

Other Number(s):: 1307

DOE Contract Number:: EE0008760

Research Org.:: DOE Geothermal Data Repository; Colorado School of Mines

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)

Collaborations:: Colorado School of Mines

Subject:: 15 GEOTHERMAL ENERGY; AI; Geothermal AI; K-Means; LST; Landsat ADR LST; Machine Learning; NumPy; Python; R; SLURM; Self Organizing Map; Shell; Shell scripts; TensorFlow; anomaly detection; artificial intelligence; blind; code; deep learning; energy; exploration; geothermal; geothermal exploration; k mean; land surface temperature; raster; remote sensing; sbatch; site detection

OSTI Identifier:: 1787330

DOI:: https://doi.org/10.15121/1787330

Citation Formats


                    Moraga, Jim. Programs and Code for Geothermal Exploration Artificial Intelligence.  United States: N. p., 2021. 
        Web.  doi:10.15121/1787330.

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                    Moraga, Jim. Programs and Code for Geothermal Exploration Artificial Intelligence.  United States.  doi:https://doi.org/10.15121/1787330

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                    Moraga, Jim. 2021.  
"Programs and Code for Geothermal Exploration Artificial Intelligence".  United States.  doi:https://doi.org/10.15121/1787330.  https://www.osti.gov/servlets/purl/1787330. Pub date:Tue Apr 27 00:00:00 EDT 2021

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@article{osti_1787330,

  title        = {Programs and Code for Geothermal Exploration Artificial Intelligence},

  author       = {Moraga, Jim},

  abstractNote = {The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including: - Land Surface Temperature K-Means classifier - Labeling AI using Self Organizing Maps (SOM) - Post-processing for Permanent Scatterer InSAR (PSInSAR) analysis with SOM - Mineral marker summarizing - Artificial Intelligence (AI) Data splitting: creates data set from a single raster file - Artificial Intelligence Model: creates AI from a single data set, after splitting in Train, Validation and Test subsets - AI Mapper: creates a classification map based on a raster file},

  doi          = {10.15121/1787330},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Apr 27 00:00:00 EDT 2021},

  month        = {Tue Apr 27 00:00:00 EDT 2021}

}

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DOI: https://doi.org/10.15121/1787330

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