Comparison of Different Methods of Application of Neural Network on Soil Profile of Khartoum State
International Journal of Science, Technology and Society
Volume 2, Issue 3, May 2014, Pages: 59-62
Received: May 7, 2014; Accepted: May 23, 2014; Published: May 30, 2014
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Authors
Hussein Elarabi, Head of Geotechnical Department, Building and Road Research Institute, University of Khartoum, Sudan; Building and Road Research Institute, University of Khartoum, Sudan
N. F. Taha, Head of Geotechnical Department, Building and Road Research Institute, University of Khartoum, Sudan; Building and Road Research Institute, University of Khartoum, Sudan
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Abstract
Within the last years, four methods have been developed to predict the soil profile and its parameters in Sudan. However, a method making such predictions with the required degree of accuracy and consistency has not yet been developed. In this paper, artificial neural networks, ANNs are used in an attempt to compare between these methods by applying them on large zone contains many sites to select a unified method. A large database of actual measured is used to develop and verify the ANN model. The predicted soil profile found by utilizing ANNs is compared between them. The results indicate that ANNs are a useful technique for predicting the soil profile and its parameters when using anyone of the compared methods.
Keywords
Artificial Neural Network, Soil Profile, Khartoum, Prediction
To cite this article
Hussein Elarabi, N. F. Taha, Comparison of Different Methods of Application of Neural Network on Soil Profile of Khartoum State, International Journal of Science, Technology and Society. Vol. 2, No. 3, 2014, pp. 59-62. doi: 10.11648/j.ijsts.20140203.15
References
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El Hassan, M., (2009),“ Prediction of Blue Nile Soil Profile Using Artificial Neural Network”, M. Sc. thesis BBRI, University of Khartoum, Khartoum, Sudan.
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Mohammed, S. Elnasr (2009), “APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN PREDICTION OF SOIL PROFILE IN SUDAN, MSc thesis BBRI, University of Khartoum, Khartoum, Sudan.
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Mohamed A. Shahin1; Holger R. Maier2; and Mark B. Jaksa3, (2002), “Predicting Settlement of Shallow Foundations using Neural Networks”, Pp: (785-793).
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Mohamed, K.M.(2005),“Artificial Intelligence Applica-tions in Geotechnical Engineering in Sudan”, MSc thesis, BBRI, University of Khartoum, Khartoum, Sudan.
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Nour Alfadul, Y.M. (2007),“Soil Profile Prediction Using Artificial Neural Networks in Sudan”,MSc thesis BBRI,University of Khartoum, Khartoum, Sudan.
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Shahin, M. A., Jaksa, M. B., and Maier, H. R. (2001). "Artificial neural network applications in geotechnical engineer-ing." Australia Geomechanics, 36(1), 49-62.
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