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 and 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. doi: 10.22059/jesphys.2009.79977
MLA
Hajian,A R , , E. Ardestani,V , , Lucas,C , and 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 and 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
