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.
| Published in | International Journal of Science, Technology and Society (Volume 2, Issue 3) |
| DOI | 10.11648/j.ijsts.20140203.15 |
| Page(s) | 59-62 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2014. Published by Science Publishing Group |
Artificial Neural Network, Soil Profile, Khartoum, Prediction
| [1] | El Hassan, M., (2009),“ Prediction of Blue Nile Soil Profile Using Artificial Neural Network”, M. Sc. thesis BBRI, University of Khartoum, Khartoum, Sudan. |
| [2] | Mohammed, S. Elnasr (2009), “APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN PREDICTION OF SOIL PROFILE IN SUDAN, MSc thesis BBRI, University of Khartoum, Khartoum, Sudan. |
| [3] | Mohamed A. Shahin1; Holger R. Maier2; and Mark B. Jaksa3, (2002), “Predicting Settlement of Shallow Foundations using Neural Networks”, Pp: (785-793). |
| [4] | Mohamed, K.M.(2005),“Artificial Intelligence Applica-tions in Geotechnical Engineering in Sudan”, MSc thesis, BBRI, University of Khartoum, Khartoum, Sudan. |
| [5] | Nour Alfadul, Y.M. (2007),“Soil Profile Prediction Using Artificial Neural Networks in Sudan”,MSc thesis BBRI,University of Khartoum, Khartoum, Sudan. |
| [6] | 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. |
APA Style
Hussein Elarabi, N. F. Taha. (2014). Comparison of Different Methods of Application of Neural Network on Soil Profile of Khartoum State. International Journal of Science, Technology and Society, 2(3), 59-62. https://doi.org/10.11648/j.ijsts.20140203.15
ACS Style
Hussein Elarabi; N. F. Taha. Comparison of Different Methods of Application of Neural Network on Soil Profile of Khartoum State. Int. J. Sci. Technol. Soc. 2014, 2(3), 59-62. doi: 10.11648/j.ijsts.20140203.15
AMA Style
Hussein Elarabi, N. F. Taha. Comparison of Different Methods of Application of Neural Network on Soil Profile of Khartoum State. Int J Sci Technol Soc. 2014;2(3):59-62. doi: 10.11648/j.ijsts.20140203.15
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ijsts.20140203.15,
author = {Hussein Elarabi and N. F. Taha},
title = {Comparison of Different Methods of Application of Neural Network on Soil Profile of Khartoum State},
journal = {International Journal of Science, Technology and Society},
volume = {2},
number = {3},
pages = {59-62},
doi = {10.11648/j.ijsts.20140203.15},
url = {https://doi.org/10.11648/j.ijsts.20140203.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsts.20140203.15},
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.},
year = {2014}
}
TY - JOUR T1 - Comparison of Different Methods of Application of Neural Network on Soil Profile of Khartoum State AU - Hussein Elarabi AU - N. F. Taha Y1 - 2014/05/30 PY - 2014 N1 - https://doi.org/10.11648/j.ijsts.20140203.15 DO - 10.11648/j.ijsts.20140203.15 T2 - International Journal of Science, Technology and Society JF - International Journal of Science, Technology and Society JO - International Journal of Science, Technology and Society SP - 59 EP - 62 PB - Science Publishing Group SN - 2330-7420 UR - https://doi.org/10.11648/j.ijsts.20140203.15 AB - 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. VL - 2 IS - 3 ER -
Email: