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Determination of Spatial Variability of Rock Depth of Chennai
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Author(s): Pijush Samui (National Institute of Technology Patna, India), Viswanathan R. (Galgotias University, India), Jagan J. (VIT University, India)and Pradeep U. Kurup (University of Massachusetts – Lowell, USA)
Copyright: 2018
Pages: 18
Source title:
Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms
Source Author(s)/Editor(s): Sujata Dash (North Orissa University, India), B.K. Tripathy (VIT University, India)and Atta ur Rahman (University of Dammam, Saudi Arabia)
DOI: 10.4018/978-1-5225-2857-9.ch023
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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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