CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

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
  1. Abu Kiefa, M. A. (1998). “General regression neural networks for driven piles in cohesionless soils.” J. Geotech. & Geoenv. Engrg. ASCE, 124(12), 1177-1185.
  2. Lee, I. M., & Lee, J. H. (1996). “Prediction of pile bearing capacity using artificial neural networks.” Computer and Geotechnics, 18(3), 189–200.
  3. Ellis, G. W., Yao, C., Zhao, R. and Penumadu, D. (1995). “Stress-strain modeling of sands using artificial neural networks.” J. Geotech. Engrg. ASCE, 121(5), 429- 435.
  4. Zhou, Y., and Wu, X. (1994). “Use of neural networks in the analysis and interpretation of site investigation data.” Computer and Geotechnics, 16, 105-122.
  5. Goh, A. T. C. (1994). “Seismic liquefaction potential assessed by neural network.” J. Geotech. & Geoenv. Engrg. ASCE, 120(9), 1467-1480.
  6. Black, W.P.M. (1962). “A Method of Estimating the CBR of Cohesive Soils from Plasticity Data.” Geotechnique, 12, 271 - 272.
  7. de Graft - Johnson, J.W.S. and Bhatia, H.S. 1969). “The Engineering Characteristics of the Lateritic Gravels of Ghana.” Proceedings of 7th International Conference on Soil Mechanics and Foundation Engineering, Mexico. August 28-29. Bangkok: Asian Institute of Technology. vol.2, 13 - 43.
  8. Agarwal, K. B. and Ghanekar, K.D. (1970). “Prediction of CBR from Plasticity Characteristics of Soil”. Proceeding of 2nd South-east Asian Conference on Soil Engineering, Singapore. June 11-15, 1970. Bangkok: Asian Institute of Technology, 571-576.
  9. National Cooperative Highway Research Program (2001). “Correlation of CBR Values with Soil Index Properties.” Guide for Mechanistic and Empirical Design for New and Rehabilitated Pavement Structures, Appendix CC-1, Final Document, West University Avenue Champaign, Illinois: Ara, Inc.
  10. Kin, M. W. (2006). “California bearing ratio correlation with soil index properties.” Master degree Project, Faculty of Civil Engineering, University Technology Malaysia.
  11. T. Taskiran (2010).”Prediction of California bearing ratio (CBR) of fine grained soils by AI methods.” journal of Advances in Engineering Software, 41, 886–892.
  12. B. Yildirim, O. Gunaydin (2011). “Estimation of California bearing ratio by using soft computing systems.” journal of Expert Systems with Applications 38, 6381–6391.
Index Terms

Computer Science
Information Sciences

Keywords

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

Powered by PhDFocusTM