Determination of Spatial Variability of Rock Depth of Chennai

Author:

Samui Pijush1,R. Viswanathan2,J. Jagan3,Kurup Pradeep U.4

Affiliation:

1. National Institute of Technology Patna, India

2. Galgotias University, India

3. VIT University, India

4. University of Massachusetts – Lowell, USA

Abstract

This study adopts four modeling techniques Ordinary Kriging(OK), Generalized Regression Neural Network (GRNN), Genetic Programming(GP) and Minimax Probability Machine Regression(MPMR) for prediction of rock depth(d) at Chennai(India). Latitude (Lx) and Longitude(Ly) have been used as inputs of the models. A semivariogram has been constructed for developing the OK model. The developed GP gives equation for prediction of d at any point in Chennai. A comparison of four modeling techniques has been carried out. The performance of MPMR is slightly better than the other models. The developed models give the spatial variability of rock depth at Chennai.

Publisher

IGI Global

Reference51 articles.

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3. Spatial variability of the undrained strength of clays.;A.Asaoka;Journal of the Geotechnical Engineering Division,1982

4. Baecher, G. B. (1984). On estimating auto–covariance of soil properties. Specialty Conference on Probabilistic Mechanics and Structural Reliability, American Society of Civil Engineers, 110, 214–218.

5. Modeling soil variability as a random field

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