University of Khartoum

Application of artificial neural network prediction of Sudan soil profile

Application of artificial neural network prediction of Sudan soil profile

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Title: Application of artificial neural network prediction of Sudan soil profile
Author: Elarabi, Hussein
Abstract: The aim of this paper is to predict the natural geotechnical profile of Sudan country, which is very important and vital for all civil engineering work. Availability of pre-predicted profile before performing drilling and boring minimize time and cost. To achieve this goal Artificial Neural Networks (ANNs) program is used. This program has capabilities to study and process the problems that have complex variable, such as Sudan topographical profile. Five main ANN models were constructed based on the soil data of 1909 boreholes from 417 sites. These models use the three dimensional coordinates as input data to predict soil profile and soil parameters at different locations. Artificial Neural Networks is found to have the acceptable ability to predict the soil classification and soil parameters in Sudan. The lack in accuracy in some predicted data when compared with the soil profile obtained from actual boreholes is due to inconsistency of coordinates and depth.
Description: Application of artificial neural network for prediction of Sudan soil profile
URI: http://hdl.handle.net/123456789/5009
Date: 2014-03-30


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