NDLI: The applicability of neural networks in the determination of soil profiles

Content Provider	Springer Nature Link
Author	Caglar, Naci Arman, Hasan
Copyright Year	2006
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.La réalisation de nombreux forages, nécessaires à l’établissement d’un profil de sol pour une région donnée, est une opération longue et coûteuse. L’article décrit comment une estimation préliminaire de profils de sol peut être obtenue à partir d’un modèle basé sur une technique d’intelligence artificielle: les réseaux de neurones artificiels ou ANN (artificial neural networks). L’ANN est un outil de traitement de données, capable d’identifier et de représenter des relations complexes entre données d’entrée d’un système et données de sortie. Il traite de problèmes multivariés pour lesquels une solution analytique n’existe pas ou serait très complexe à établir. Le problème du tassement des sols dans la région d’Adapazari a été choisi pour montrer les capacités du modèle. Les résultats obtenus à partir de l’ANN sont prometteurs par comparaison avec les profils de sols obtenus à partir des sondages.
Starting Page	295
Ending Page	301
Page Count	7
File Format	PDF
ISSN	14359529
Journal	Bulletin of the International Association of Engineering Geology - Bulletin de l'Association Internationale de Géologie de l'Ingénieur
Volume Number	66
Issue Number	3
e-ISSN	14359537
Language	English
Publisher	Springer-Verlag
Publisher Date	2006-11-25
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Données de sondages Profils de sols Réseaux de neurones artificiels Rétropropagation Nature Conservation Geoecology/Natural Processes Structural Foundations, Hydraulic Engineering Applied Geosciences
Content Type	Text
Resource Type	Article
Subject	Geology Geotechnical Engineering and Engineering Geology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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