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Correlation of Mechanical Properties of Weathered Basaltic Terrain for Strength Characterization of Foundation using ANN

by Saklecha P.P., Katpatal Y.B., Rathore S.S., Agarawal D.K.
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 33 - Number 10
Year of Publication: 2011
Authors: Saklecha P.P., Katpatal Y.B., Rathore S.S., Agarawal D.K.
10.5120/4054-5820

Saklecha P.P., Katpatal Y.B., Rathore S.S., Agarawal D.K. . Correlation of Mechanical Properties of Weathered Basaltic Terrain for Strength Characterization of Foundation using ANN. International Journal of Computer Applications. 33, 10 ( November 2011), 7-12. DOI=10.5120/4054-5820

@article{ 10.5120/4054-5820,
author = { Saklecha P.P., Katpatal Y.B., Rathore S.S., Agarawal D.K. },
title = { Correlation of Mechanical Properties of Weathered Basaltic Terrain for Strength Characterization of Foundation using ANN },
journal = { International Journal of Computer Applications },
issue_date = { November 2011 },
volume = { 33 },
number = { 10 },
month = { November },
year = { 2011 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume33/number10/4054-5820/ },
doi = { 10.5120/4054-5820 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:19:49.409213+05:30
%A Saklecha P.P.
%A Katpatal Y.B.
%A Rathore S.S.
%A Agarawal D.K.
%T Correlation of Mechanical Properties of Weathered Basaltic Terrain for Strength Characterization of Foundation using ANN
%J International Journal of Computer Applications
%@ 0975-8887
%V 33
%N 10
%P 7-12
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents the application of artificial neural network (ANN) to study the strength characterization of a foundation soils in a basaltic terrain. The prediction models were developed for foundation strength characteristic California Bearing Ratio (CBR) using correlations with mechanical properties of foundation soil viz. optimum moisture content (OMC), maximum dry density (MDD), liquid limit (LL), plastic limit (PL), and plasticity index (PI). For this study, 387 laboratory test data sets were collected for different locations in Wardha district in the state of Maharashtra, India. It has been shown that ANN was able to learn the relations between strength characteristic CBR and mechanical properties of foundation soil. The results indicated a strong correlation (r = 0.87). The performance of the developed ANN model has been validated by actual laboratory tests and a good correlation r = 0.9971 was obtained.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Prediction Correlation Foundation soil Subgrade Feed forward backpropagation neural network (FFBP)

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