Developing of Prediction Models for Soil Profile and Its Parameters Using Artificial Neural Networks
Volume 2, Issue 3, June 2014, Pages: 43-48
Received: May 22, 2014;
Accepted: Jun. 9, 2014;
Published: Jun. 20, 2014
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Hussein Elarabi, Geotechnical Department, Building and Road Research Institute, University of Khartoum, Sudan
Nahed F. Taha, Building and Road Research Institute, University of Khartoum, Sudan
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Artificial neural networks (ANNs) are a form of artificial intelligence (AI), which in their architecture attempt to simulate the biological structure of the human brain and nervous system. In this report, back-propagation neural networks are used to predict soil classification and soil parameters of Khartoum State. The study was based on the available data collected from specified areas in Khartoum, and then the results were compared with data brought from actual boreholes to check the ANN model validity. The results indicate that artificial neural networks are a promising method in predicting soil classification and soil parameters of Khartoum State.
Artificial Neural Networks, Soil Profile, Soil Parameters, Khartoum, Sudan
To cite this article
Nahed F. Taha,
Developing of Prediction Models for Soil Profile and Its Parameters Using Artificial Neural Networks, Science Research.
Vol. 2, No. 3,
2014, pp. 43-48.
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