Abstract
The drilling of a number of boreholes to determine the soil profile of a given area is time consuming and costly. This paper describes estimated soil profiles obtained using a model based on artificial neural networks (ANN). ANN is a powerful data-modelling tool capable of capturing and representing complex relationships between input and output. It deals with many multi-variate problems for which an exact analytical model does not exist or is very difficult and time consuming to develop. The main settlement in the Adapazari region was selected to demonstrate the capability of such model. The results obtained using ANN are promising when compared with the soil profile obtained from boreholes.
Original language | English |
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Pages (from-to) | 295-301 |
Number of pages | 7 |
Journal | Bulletin of Engineering Geology and the Environment |
Volume | 66 |
Issue number | 3 |
DOIs | |
Publication status | Published - Aug 2007 |
Externally published | Yes |
Keywords
- Artificial neural network
- Back-propagation
- Borehole data
- Soil profiling
ASJC Scopus subject areas
- Geotechnical Engineering and Engineering Geology
- Geology