Determination of rock depth using artificial intelligence techniques

Determination of rock depth using artificial intelligence techniques

This article adopts three artificial intelligence techniques, Gaussian Process Regression (GPR), Least Square Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), for prediction of rock depth (d) at any point in Chennai. GPR, ELM and LSSVM have been used as regression techniques. Latit...

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Bibliographic Details
Main Authors: R. Viswanathan, Pijush Samui
Format: Article
Language:English
Published: Elsevier 2016-01-01
Series:Geoscience Frontiers
Subjects:
Rock depth
Spatial variability
Least square support vector machine
Gaussian process regression
Extreme learning machine
Online Access:http://www.sciencedirect.com/science/article/pii/S1674987115000456
Description
Summary:This article adopts three artificial intelligence techniques, Gaussian Process Regression (GPR), Least Square Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), for prediction of rock depth (d) at any point in Chennai. GPR, ELM and LSSVM have been used as regression techniques. Latitude and longitude are also adopted as inputs of the GPR, ELM and LSSVM models. The performance of the ELM, GPR and LSSVM models has been compared. The developed ELM, GPR and LSSVM models produce spatial variability of rock depth and offer robust models for the prediction of rock depth.
ISSN:1674-9871

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