Private Outsourced Kriging Interpolation

2017 ◽  
pp. 75-90
Author(s):  
James Alderman ◽  
Benjamin R. Curtis ◽  
Oriol Farràs ◽  
Keith M. Martin ◽  
Jordi Ribes-González
Keyword(s):  
Kriging Interpolation

scholarly journals Pseudo 3D seismic using kriging interpolation

2021 ◽  
Vol 1725 ◽  
pp. 012075
Author(s):  
F Abdullah ◽  
E Yulianto ◽  
Novrizal ◽  
A Riyanto
Keyword(s):  
Kriging Interpolation ◽  
3D Seismic

scholarly journals Application of Dynamically Constrained Interpolation Methodology in Simulating National-Scale Spatial Distribution of PM2.5 Concentrations in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 272
Author(s):  
Ning Li ◽  
Junli Xu ◽  
Xianqing Lv
Keyword(s):  
Transport Model ◽  
Ground Level ◽  
Kriging Interpolation ◽  
Model Parameters ◽  
National Scale ◽  
Constrained Interpolation ◽  
Simulation Accuracy ◽  
Interpolation Accuracy ◽  
Geographical Regions ◽  
The Right

Numerous studies have revealed that the sparse spatiotemporal distributions of ground-level PM2.5 measurements affect the accuracy of PM2.5 simulation, especially in large geographical regions. However, the high precision and stability of ground-level PM2.5 measurements make their role irreplaceable in PM2.5 simulations. This article applies a dynamically constrained interpolation methodology (DCIM) to evaluate sparse PM2.5 measurements captured at scattered monitoring sites for national-scale PM2.5 simulations and spatial distributions. The DCIM takes a PM2.5 transport model as a dynamic constraint and provides the characteristics of the spatiotemporal variations of key model parameters using the adjoint method to improve the accuracy of PM2.5 simulations. From the perspective of interpolation accuracy and effect, kriging interpolation and orthogonal polynomial fitting using Chebyshev basis functions (COPF), which have been proved to have high PM2.5 simulation accuracy, were adopted to make a comparative assessment of DCIM performance and accuracy. Results of the cross validation confirm the feasibility of the DCIM. A comparison between the final interpolated values and observations show that the DCIM is better for national-scale simulations than kriging or COPF. Furthermore, the DCIM presents smoother spatially interpolated distributions of the PM2.5 simulations with smaller simulation errors than the other two methods. Admittedly, the sparse PM2.5 measurements in a highly polluted region have a certain degree of influence on the interpolated distribution accuracy and rationality. To some extent, adding the right amount of observations can improve the effectiveness of the DCIM around existing monitoring sites. Compared with the kriging interpolation and COPF, the results show that the DCIM used in this study would be more helpful for providing reasonable information for monitoring PM2.5 pollution in China.

Privacy-preserving kriging interpolation on partitioned data

2014 ◽  
Vol 62 ◽  
pp. 38-46 ◽  
Author(s):  
Bulent Tugrul ◽  
Huseyin Polat
Keyword(s):  
Privacy Preserving ◽  
Kriging Interpolation ◽  
Partitioned Data

scholarly journals Mapping and Estimation of Monthly Global Solar Irradiation in Different Zones in Souss-Massa Area, Morocco, Using Artificial Neural Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-19 ◽  
Author(s):  
O. Nait Mensour ◽  
S. Bouaddi ◽  
B. Abnay ◽  
B. Hlimi ◽  
A. Ihlal
Keyword(s):  
Solar Energy ◽  
Solar Irradiation ◽  
Kriging Interpolation ◽  
Solar Pv ◽  
Energy Potential ◽  
Global Solar Irradiation ◽  
Interpolation Technique ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Hidden Layer

Solar radiation data play an important role in solar energy research. However, in regions where the meteorological stations providing these data are unavailable, strong mapping and estimation models are needed. For this reason, we have developed a model based on artificial neural network (ANN) with a multilayer perceptron (MLP) technique to estimate the monthly average global solar irradiation of the Souss-Massa area (located in the southwest of Morocco). In this study, we have used a large database provided by NASA geosatellite database during the period from 1996 to 2005. After testing several models, we concluded that the best model has 25 nodes in the hidden layer and results in a minimum root mean square error (RMSE) equal to 0.234. Furthermore, almost a perfect correlation coefficient R=0.988 was found between measured and estimated values. This developed model was used to map the monthly solar energy potential of the Souss-Massa area during a year as estimated by the ANN and designed with the Kriging interpolation technique. By comparing the annual average solar irradiation between three selected sites in Souss-Massa, as estimated by our model, and six European locations where large solar PV plants are deployed, it is apparent that the Souss-Massa area is blessed with higher solar potential.

scholarly journals Preliminary groundwater modelling by considering the interaction with superficial water: Aosta plain case (northern Italy)

2013 ◽  
Author(s):  
Tullia Bonomi ◽  
Letizia Fumagalli ◽  
Valeria Benastini ◽  
Marco Rotiroti ◽  
Pietro Capodaglio ◽  
...  
Keyword(s):  
Water Supply ◽  
Three Dimensional ◽  
Decision Support Tool ◽  
Kriging Interpolation ◽  
Public Water Supply ◽  
Scientific Cooperation ◽  
Public Authorities ◽  
Support Tool ◽  
Hydrogeological Characteristics ◽  
The Impact

The study is developed through scientific cooperation between the University of Milano-Bicocca and the Regional Agency for Environmental Protection (ARPA) of the Valle d’Aosta Region. Its aim is to produce a decision-support tool to help the Public Administration’manage groundwater and public water supply. The study area is the plain of Aosta, between the cities of Aymavilles and Brissogne; in this area groundwater represents the main source of public water supply. The valley is oriented east-west, along the Baltea for a length of 13.1 km and a width of 4.6 km. The textural and hydrogeological properties of the deposits are strictly connected to glacial deposition and to the subsequent sedimentary processes which took place in glacial, lacustrine and fluvial systems. The study is based on available well information in the Aosta plain - including water wells (133) and piezometers (121) - which have been coded and stored in the well database TANGRAM,. The database facilitates interpretation of the well data, and it allows three-dimensional mapping of subsurface hydrogeological characteristics through database codification and ordinary kriging interpolation. The study is designed to achieve two objectives. The first is to provide the Aosta Public Authorities with a well database in order to simplify groundwater management. The second is to provide Public Authorities with a groundwater flow model of the local aquifer. The model integrates surface and subsurface flows in order to fully account for all important stresses, both natural and anthropogenic, on the groundwater system. It provides a tool for testing hypotheses (such as the impact of new wells) and thereby allows science-based management of the aquifer resource.

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