The objective of this paper is to compare between two studies that had been carried out using ANNs in prediction of Sudan soil profile. This importance in the design and implementation of all engineering projects which reduce cost and time. Artificial Neural Networks (ANNs) program is applied to realize this aim. The data of 1909 boreholes from 417 sites was used firstly for a single model and then divided to five zones to be used for localized models. The input data is the coordinate and depth and the output data is the soil classification and soil parameters. The result showed that ANNs can be used as a good decision support and source of information for soils profiles. It is more efficient tools to be used for small zones than all area.
| Published in |
Science Innovation (Volume 2, Issue 5-1)
This article belongs to the Special Issue Innovation Sciences--Managing Technology in Society |
| DOI | 10.11648/j.si.s.2014020501.11 |
| Page(s) | 1-4 |
| 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 |
Soil Profile, Artificial Neural Networks, Sudan, Prediction
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APA Style
Hussien Elarabi, Safa A. Abdelgalil. (2014). Comparison of two Different Application of Neural Network on Sudan Soil Profile. Science Innovation, 2(5-1), 1-4. https://doi.org/10.11648/j.si.s.2014020501.11
ACS Style
Hussien Elarabi; Safa A. Abdelgalil. Comparison of two Different Application of Neural Network on Sudan Soil Profile. Sci. Innov. 2014, 2(5-1), 1-4. doi: 10.11648/j.si.s.2014020501.11
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Download@article{10.11648/j.si.s.2014020501.11,
author = {Hussien Elarabi and Safa A. Abdelgalil},
title = {Comparison of two Different Application of Neural Network on Sudan Soil Profile},
journal = {Science Innovation},
volume = {2},
number = {5-1},
pages = {1-4},
doi = {10.11648/j.si.s.2014020501.11},
url = {https://doi.org/10.11648/j.si.s.2014020501.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.s.2014020501.11},
abstract = {The objective of this paper is to compare between two studies that had been carried out using ANNs in prediction of Sudan soil profile. This importance in the design and implementation of all engineering projects which reduce cost and time. Artificial Neural Networks (ANNs) program is applied to realize this aim. The data of 1909 boreholes from 417 sites was used firstly for a single model and then divided to five zones to be used for localized models. The input data is the coordinate and depth and the output data is the soil classification and soil parameters. The result showed that ANNs can be used as a good decision support and source of information for soils profiles. It is more efficient tools to be used for small zones than all area.},
year = {2014}
}
TY - JOUR T1 - Comparison of two Different Application of Neural Network on Sudan Soil Profile AU - Hussien Elarabi AU - Safa A. Abdelgalil Y1 - 2014/07/07 PY - 2014 N1 - https://doi.org/10.11648/j.si.s.2014020501.11 DO - 10.11648/j.si.s.2014020501.11 T2 - Science Innovation JF - Science Innovation JO - Science Innovation SP - 1 EP - 4 PB - Science Publishing Group SN - 2328-787X UR - https://doi.org/10.11648/j.si.s.2014020501.11 AB - The objective of this paper is to compare between two studies that had been carried out using ANNs in prediction of Sudan soil profile. This importance in the design and implementation of all engineering projects which reduce cost and time. Artificial Neural Networks (ANNs) program is applied to realize this aim. The data of 1909 boreholes from 417 sites was used firstly for a single model and then divided to five zones to be used for localized models. The input data is the coordinate and depth and the output data is the soil classification and soil parameters. The result showed that ANNs can be used as a good decision support and source of information for soils profiles. It is more efficient tools to be used for small zones than all area. VL - 2 IS - 5-1 ER -
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