Implementation of MLP-NN on Field data for dipole dipole and Alt3 Wenner configurations
- New Mexico State Univ., Las Cruces, NM (United States); New Mexico State Univ., Las Cruces, NM (United States)
Training data for both dipole dipole and Alt3 wenner configurations included. Field dataset for both dipole dipole and Alt3 wenner configurations included (Test dataset). Python code for implementation of MLP-NN included. Results for inversion of both configurations included.
- Research Organization:
- New Mexico State University, Las Cruces, NM (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- DOE Contract Number:
- SC0023132
- OSTI ID:
- 2520476
- Country of Publication:
- United States
- Language:
- English
Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets
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journal | October 2024 |
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