Affiliations: Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Selangor DarulEhsan, Malaysia | Department of Electrical and Electronics and System Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Selangor DarulEhsan, Malaysia | Department of Electrical and Electronics Engineering, Faculty of Computer Science and Engineering, PSTU, Bangladesh
Note: [] Corresponding author. S.M. Taohidul Islam, Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor DarulEhsan, Malaysia. Tel.: +6038921 6200/6213; Fax: +603 8921 6147; E-mail: [email protected] (S.M. Taohidul Islam); [email protected] (Z.Chik).
Abstract: This paper presents a technique to obtain the outcomes of soil dry density and optimum moisture contents with artificial neural network (ANN) for compacted soil monitoring through soil resistivity measurement in geotechnical engineering. The compacted soil monitoring through soil electrical resistivity shows the important role in the construction of highway embankments, earth dams and many other engineering structure. Generally, soil compaction is estimated through the determination of maximum dry density at optimum moisture contents in laboratory test. To estimate the soil compaction in conventional soil monitoring technique is time consuming and costly for the laboratory testing with a lot of samples of compacted soil. In this work, an ANN model is developed for predicting the relationship between dry density of compacted soil and soil electrical resistivity based on experimental data in soil profile. The regression analysis between the output and target values shows that the R2 values are 0.99 and 0.93 for the training and testing sets respectively for the implementation of ANN in soil profile. The significance of our research is to obtain an intelligent model for getting faster, cost-effective and consistent outcomes in soil compaction monitoring through electrical resistivity for a wide range of applications in geotechnical investigation.
Keywords: Soil compaction, ANN modeling, electrical resistivity, dry density
