1
Instructor, Physics Department, Islamic Azad University, Najaf Abad Branch, Isfahan, Iran
2
Associate Professor, Earth Physics Department, Institute of Geophysics, University of Tehran and Center of Excellence in Survey Engineering and Disaster Management, Tehran, Iran
3
Professor of control, Electrical Engineering Department, University of Tehran, Iran
A full automatic algorithm is designed to detect subsurface Qanats (sub terrains) via Artificial Neural Networks .We first gained the residual gravity anomaly from microgravity data and then applied it to a Multi Layer Perceptron (MLP) which was trained for the models of sphere and cylinder.
As a field example, the depth of a subsurface Qanat buried under the north entrance of the Geophysics Institute is determined through MLP (trained with noisy data).
Hajian, A. R., E. Ardestani, V., Lucas, C., & Saghaiannejad, S. M. (2009). Detection of subsurface Qanats by Artificial Neural Network via Microgravity data. Journal of the Earth and Space Physics, 35(1), 9-15. https://doi.org/10.22059/jesphys.2009.79977
MLA
Hajian, A. R., E. Ardestani, V., Lucas, C., & Saghaiannejad, S. M. "Detection of subsurface Qanats by Artificial Neural Network via Microgravity data", Journal of the Earth and Space Physics, 35, 1, 2009, 9-15. doi: 10.22059/jesphys.2009.79977
HARVARD
Hajian A. R., E. Ardestani V., Lucas C., Saghaiannejad S. M. (2009). 'Detection of subsurface Qanats by Artificial Neural Network via Microgravity data', Journal of the Earth and Space Physics, 35(1), pp. 9-15. doi: 10.22059/jesphys.2009.79977
CHICAGO
A. R. Hajian, V. E. Ardestani, C. Lucas & S. M. Saghaiannejad, "Detection of subsurface Qanats by Artificial Neural Network via Microgravity data," Journal of the Earth and Space Physics, 35 1 (2009): 9-15, doi: 10.22059/jesphys.2009.79977
VANCOUVER
Hajian A. R., E. Ardestani V., Lucas C., Saghaiannejad S. M. Detection of subsurface Qanats by Artificial Neural Network via Microgravity data. JESP. 2009;35(1):9-15 (In Persian). doi: 10.22059/jesphys.2009.79977
