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A platform for research: civil engineering, architecture and urbanism
The estimation of sampling density in improving geostatistical prediction for geotechnical characterization
Optimum sampling grid was established using geostatistical estimation in order to improve the accuracy of spatial prediction to characterize Rock Quality Designation (RQD). Ordinary Kriging (OK) present in the software GEOVIA Surpac™ module was implemented to undertake geostatistical estimation. The cross-validation method was used to determine the level of accuracy in the process of establishing the optimum sampling density. Generally, the optimal sampling density for this project is 50.1 m, although taking into consideration the results of cross-validation it is deduced that the sampling density laying within 50.1m to 235.68 m is ideal for this project to characterize the RQD. Taking into account the cost of geotechnical drilling, the leave one out cross-validation (LOOCV) method can be used to establish the range of sampling density for RQD. The study area was subdividing into three scenarios and each scenario had training and testing samples for the application of cross-validation technique.
The estimation of sampling density in improving geostatistical prediction for geotechnical characterization
Optimum sampling grid was established using geostatistical estimation in order to improve the accuracy of spatial prediction to characterize Rock Quality Designation (RQD). Ordinary Kriging (OK) present in the software GEOVIA Surpac™ module was implemented to undertake geostatistical estimation. The cross-validation method was used to determine the level of accuracy in the process of establishing the optimum sampling density. Generally, the optimal sampling density for this project is 50.1 m, although taking into consideration the results of cross-validation it is deduced that the sampling density laying within 50.1m to 235.68 m is ideal for this project to characterize the RQD. Taking into account the cost of geotechnical drilling, the leave one out cross-validation (LOOCV) method can be used to establish the range of sampling density for RQD. The study area was subdividing into three scenarios and each scenario had training and testing samples for the application of cross-validation technique.
The estimation of sampling density in improving geostatistical prediction for geotechnical characterization
Fisonga, Marsheal (author) / Wang, Fei (author) / Mutambo, Victor (author)
International Journal of Geotechnical Engineering ; 15 ; 724-731
2021-07-03
8 pages
Article (Journal)
Electronic Resource
Unknown
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