Determination of rock depth using artificial intelligence techniques

被引:0
作者
RViswanathan [1 ]
Pijush Samui [2 ]
机构
[1] School of Information Technology & Engineering,VIT University
[2] Centre for Disaster Mitigation and Management,VIT
关键词
D O I
暂无
中图分类号
P631.3 [电法勘探]; TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
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收藏
页码:61 / 66
页数:6
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