DEPTH ESTIMATION OF SUBSURFACE CAVITIES VIA MULTI-LAYER PERCEPTRON NEURAL NETWORK FROM MICROGRAVITY DATA

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HAJIAN ALIREZA; ARDESTANI V.E.; LUCAS CARO; HAJIAN MOHADDESEH

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Seminar Paper

Paper Information

Seminar: IRANIAN GEOPHYSICS CONFERENCE
Year:2006 | Issue:12

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Title

DEPTH ESTIMATION OF SUBSURFACE CAVITIES VIA MULTI-LAYER PERCEPTRON NEURAL NETWORK FROM MICROGRAVITY DATA

Author(s)

HAJIAN ALIREZA | ARDESTANI V.E. | LUCAS CARO | HAJIAN MOHADDESEH

Keywords

MICROGRAVITY

DEPTH ESTIMATION

SUBSURFACE CAVITIES

ARTIFICIAL NEURAL NETWORKS

MULTI-LAYER PERCEPTRON

Abstract

WE AIM TO ESTIMATE THE DEPTH OF SUBSURFACE CAVITIES FROM MICROGRAVITY DATA THROUGH A MULTI-LAYER PERCEPTRON (MLP) NEURAL NETWORK. INFACT, THIS METHOD IS AN INTELLIGENT WAY TO INTERPRET MICROGRAVITY DATA AND GAIN AN ESTIMATION OF DEPTH. THE MLP NEURAL NETWORK WAS TRAINED FOR TWO MAIN MODELS OF CAVITIES: SPHERE AND CYLINDER IN A DOMAIN OF RADIUS AND DEPTH. WE TESTED DIFFERENT MLP’S WITH DIFFERENT NUMBER OF NEURONS IN THE HIDDEN LAYER AND OBTAINED THE OPTIMUM VALUE FOR NUMBER OF NEURONS IN THE HIDDEN LAYER. THEN IT WAS TESTED IN PRESENT OF 30% NOISE (S/N=.3), AND ALSO TESTED FOR REAL DATA. IT PRESENTED GOOD RESULTS FOR DEPTH ESTIMATION OF SUBSURFACE CAVITIES.

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APA: Copy

HAJIAN, ALIREZA, ARDESTANI, V.E., LUCAS, CARO, & HAJIAN, MOHADDESEH. (2006). DEPTH ESTIMATION OF SUBSURFACE CAVITIES VIA MULTI-LAYER PERCEPTRON NEURAL NETWORK FROM MICROGRAVITY DATA. IRANIAN GEOPHYSICS CONFERENCE. SID. https://sid.ir/paper/906532/en

Vancouver: Copy

HAJIAN ALIREZA, ARDESTANI V.E., LUCAS CARO, HAJIAN MOHADDESEH. DEPTH ESTIMATION OF SUBSURFACE CAVITIES VIA MULTI-LAYER PERCEPTRON NEURAL NETWORK FROM MICROGRAVITY DATA. 2006. Available from: https://sid.ir/paper/906532/en

IEEE: Copy

ALIREZA HAJIAN, V.E. ARDESTANI, CARO LUCAS, and MOHADDESEH HAJIAN, “DEPTH ESTIMATION OF SUBSURFACE CAVITIES VIA MULTI-LAYER PERCEPTRON NEURAL NETWORK FROM MICROGRAVITY DATA,” presented at the IRANIAN GEOPHYSICS CONFERENCE. 2006, [Online]. Available: https://sid.ir/paper/906532/en

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