Determination of Spatial Variability of Rock Depth of Chennai

Determination of Spatial Variability of Rock Depth of Chennai

Pijush Samui, Viswanathan R., Jagan J., Pradeep U. Kurup
ISBN13: 9781799880486|ISBN10: 1799880486|EISBN13: 9781799880998
DOI: 10.4018/978-1-7998-8048-6.ch006
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MLA

Samui, Pijush, et al. "Determination of Spatial Variability of Rock Depth of Chennai." Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, edited by Information Resources Management Association, IGI Global, 2021, pp. 98-115. https://doi.org/10.4018/978-1-7998-8048-6.ch006

APA

Samui, P., R., V., J., J., & Kurup, P. U. (2021). Determination of Spatial Variability of Rock Depth of Chennai. In I. Management Association (Ed.), Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms (pp. 98-115). IGI Global. https://doi.org/10.4018/978-1-7998-8048-6.ch006

Chicago

Samui, Pijush, et al. "Determination of Spatial Variability of Rock Depth of Chennai." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, edited by Information Resources Management Association, 98-115. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-8048-6.ch006

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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.

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