Depth estimation of subsurface cavities via Multi Layer Perceptron Neural Network from microgravity data

سال انتشار: 1384
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 3,046

فایل این مقاله در 7 صفحه با فرمت PDF قابل دریافت می باشد

این مقاله در بخشهای موضوعی زیر دسته بندی شده است:

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:


تاریخ نمایه سازی: 11 دی 1384

چکیده مقاله:

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 ٣٠٪ noise(S/N=.٣), and also tested for real data. It presented good results for depth estimation of subsurface cavitie


Alireza Hajian

Institute of geophysics, Tehran University


Head of gravity, Institute of geophysics, Tehran University

Caro Lucas

Head of control, Electrical Engineering Department, Tehran university

Mohaddeseh Hajian

Geology Department,Isfahan University