Works matching DE "VARIOGRAMS"
Results: 303
Leveraging Deep Learning for Automated Experimental Semivariogram Fitting.
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- Atmosphere, 2025, v. 16, n. 2, p. 191, doi. 10.3390/atmos16020191
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The effects of experimental whole-lake mixing on horizontal spatial patterns of fish and Zooplankton.
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- Aquatic Sciences, 2017, v. 79, n. 3, p. 543, doi. 10.1007/s00027-016-0516-x
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Geological and geostatistical analysis for equivalent uranium and thorium mineralization, Gattar-V Eastern Desert, Egypt.
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- Mining of Mineral Deposits, 2023, v. 17, n. 4, p. 18, doi. 10.33271/mining17.04.018
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Spatial assessment of soil salinity in the Harran Plain using multiple kriging techniques.
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- Environmental Monitoring & Assessment, 2013, v. 185, n. 1, p. 777, doi. 10.1007/s10661-012-2591-3
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- Article
Geomorphological landscape features explain floristic patterns in French Guiana rainforest.
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- Biodiversity & Conservation, 2015, v. 24, n. 5, p. 1215, doi. 10.1007/s10531-014-0854-8
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- Article
Special Issue "Probability Theory and Stochastic Modeling with Applications".
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- Mathematics (2227-7390), 2023, v. 11, n. 14, p. 3196, doi. 10.3390/math11143196
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On Robustness for Spatio-Temporal Data.
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- Mathematics (2227-7390), 2022, v. 10, n. 10, p. 1785, doi. 10.3390/math10101785
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A Quadratic–Exponential Model of Variogram Based on Knowing the Maximal Variability: Application to a Rainfall Time Series.
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- Mathematics (2227-7390), 2021, v. 9, n. 19, p. 2466, doi. 10.3390/math9192466
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Multi-Parameter Analysis of Groundwater Resources Quality in the Auvergne-Rhône-Alpes Region (France) Using a Large Database.
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- Resources (2079-9276), 2023, v. 12, n. 12, p. 143, doi. 10.3390/resources12120143
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- Article
A SIMULATED ANNEALING BASED OPTIMIZATION ALGORITHM FOR AUTOMATIC VARIOGRAM MODEL FITTING.
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- Archives of Mining Sciences, 2016, v. 61, n. 3, p. 635, doi. 10.1515/amsc-2016-0045
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- Article
The Research into the Quality of Rock Surfaces Obtained by Abrasive Water Jet Cutting.
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- Archives of Mining Sciences, 2014, v. 59, n. 4, p. 925, doi. 10.2478/amsc-2014-0064
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- Article
Quantifying the criteria for classification of mineral resources and reserves through the estimation of block model uncertainty using geostatistical methods: a case study of Khoshoumi Uranium deposit in Yazd, Iran.
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- Geosystem Engineering, 2020, v. 23, n. 4, p. 216, doi. 10.1080/12269328.2020.1748524
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Structure learning for extremal tree models.
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- Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2022, v. 84, n. 5, p. 2055, doi. 10.1111/rssb.12556
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- Article
Assessment of the regional subsidence in the lacustrine zone of Mexico City using a geostatistical model.
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- Environmental Earth Sciences, 2022, v. 81, n. 15, p. 1, doi. 10.1007/s12665-022-10492-9
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- Article
Groundwater quality assessment of Birjand plain aquifer using kriging estimation and sequential Gaussian simulation methods.
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- Environmental Earth Sciences, 2020, v. 79, n. 10, p. 1, doi. 10.1007/s12665-020-08905-8
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- Article
Transport modeling of <sup>137</sup>Cs in soil after Fukushima Dai-Ichi Nuclear Power Plant accident by point cumulative semi-variogram method.
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- Environmental Earth Sciences, 2019, v. 78, n. 6, p. N.PAG, doi. 10.1007/s12665-019-8232-1
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Regularisation and Deregularisation of Covariances and Variograms for Univariate Random Functions in One-dimensional Space.
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- Mathematical Geosciences, 2023, v. 55, n. 5, p. 609, doi. 10.1007/s11004-022-10043-9
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Quantifying Mineral Resources and Their Uncertainty Using Two Existing Machine Learning Methods.
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- Mathematical Geosciences, 2022, v. 54, n. 2, p. 363, doi. 10.1007/s11004-021-09971-9
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High-Order Data-Driven Spatial Simulation of Categorical Variables.
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- Mathematical Geosciences, 2022, v. 54, n. 1, p. 23, doi. 10.1007/s11004-021-09943-z
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Dionissios T. Hristopulos: Random Fields for Spatial Data Modeling. A Primer for Scientists and Engineers: Springer Nature B.V. 2020, Springer, Dordrecht, ISBN: 978-94-024-1916-0.
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- 2021
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- Book Review
Numerical Analysis of Fluvial Landscapes.
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- Mathematical Geosciences, 2017, v. 49, n. 7, p. 913, doi. 10.1007/s11004-017-9698-6
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Indicator Variogram Models: Do We Have Much Choice?
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- Mathematical Geosciences, 2017, v. 49, n. 4, p. 441, doi. 10.1007/s11004-017-9678-x
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A Specific Volume to Measure the Spatial Sampling of Deposits.
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- Mathematical Geosciences, 2016, v. 48, n. 7, p. 791, doi. 10.1007/s11004-016-9647-9
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Inverse Modeling of Moving Average Isotropic Kernels for Non-parametric Three-Dimensional Gaussian Simulation.
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- Mathematical Geosciences, 2016, v. 48, n. 5, p. 559, doi. 10.1007/s11004-015-9606-x
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Anisotropy Models for Spatial Data.
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- Mathematical Geosciences, 2016, v. 48, n. 3, p. 305, doi. 10.1007/s11004-015-9594-x
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Characterization of Non-Gaussian Geologic Facies Distribution Using Ensemble Kalman Filter with Probability Weighted Re-Sampling.
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- Mathematical Geosciences, 2015, v. 47, n. 2, p. 193, doi. 10.1007/s11004-014-9548-8
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- Article
Solving Speed and Memory Issues in Multiple-Point Statistics Simulation Program SNESIM.
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- Mathematical Geosciences, 2014, v. 46, n. 2, p. 171, doi. 10.1007/s11004-013-9489-7
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- Article
Analysis and Estimation of Multi-unit Deposits: Application to a Porphyry Copper Deposit.
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- Mathematical Geosciences, 2013, v. 45, n. 8, p. 927, doi. 10.1007/s11004-013-9475-0
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Joint Consistent Mapping of High-Dimensional Geochemical Surveys.
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- Mathematical Geosciences, 2013, v. 45, n. 8, p. 983, doi. 10.1007/s11004-013-9485-y
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Conditioning Surface-Based Geological Models to Well and Thickness Data.
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- Mathematical Geosciences, 2013, v. 45, n. 7, p. 873, doi. 10.1007/s11004-013-9455-4
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Automatic Variogram Modeling by Iterative Least Squares: Univariate and Multivariate Cases.
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- Mathematical Geosciences, 2013, v. 45, n. 4, p. 453, doi. 10.1007/s11004-012-9434-1
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- Article
Isotropic Variogram Matrix Functions on Spheres.
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- Mathematical Geosciences, 2013, v. 45, n. 3, p. 341, doi. 10.1007/s11004-013-9441-x
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Non-stationary Geostatistical Modeling Based on Distance Weighted Statistics and Distributions.
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- Mathematical Geosciences, 2013, v. 45, n. 1, p. 31, doi. 10.1007/s11004-012-9428-z
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- Article
Using Simultaneous Diagonalization to Identify a Space-Time Linear Coregionalization Model.
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- Mathematical Geosciences, 2013, v. 45, n. 1, p. 69, doi. 10.1007/s11004-012-9408-3
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On the Likelihood and Fluctuations of Gaussian Realizations.
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- Mathematical Geosciences, 2012, v. 44, n. 8, p. 1005, doi. 10.1007/s11004-012-9424-3
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- Article
Variogram Matrix Functions for Vector Random Fields with Second-Order Increments.
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- Mathematical Geosciences, 2012, v. 44, n. 4, p. 411, doi. 10.1007/s11004-011-9377-y
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- Article
Integration of Sequence Stratigraphic Analysis and 3D Geostatistical Modeling of Pliocene–Pleistocene Delta, F3 Block, Netherlands.
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- Acta Geologica Sinica (English Edition), 2023, v. 97, n. 1, p. 256, doi. 10.1111/1755-6724.14863
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- Article
Investigation of Soil Salinity to Distinguish Boundary Line between Saline and Agricultural Lands in Bonab Plain, Southeast Urmia Lake, Iran.
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- Journal of Applied Sciences & Environmental Management, 2016, v. 20, n. 4, p. 1037, doi. 10.4314/jasem.v20i4.16
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- Article
Development of a brain MRI-based hidden Markov model for dementia recognition.
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- BioMedical Engineering OnLine, 2013, v. 12, p. 1, doi. 10.1186/1475-925X-12-S1-S2
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- Article
High-resolution grid of H/V spectral ratios and spatial variability on microtremors at Port of Spain, Trinidad.
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- Journal of Seismology, 2017, v. 21, n. 6, p. 1541, doi. 10.1007/s10950-017-9681-1
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- Article
Rock Mass Quality Prediction of Open-Pit Gold Mine Slope Based on the Kriging Interpolation Method.
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- Geotechnical & Geological Engineering, 2020, v. 38, n. 6, p. 5851, doi. 10.1007/s10706-020-01397-0
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- Article
Influence of available data on the geostatistical-based design of optimal spatiotemporal groundwater-level-monitoring networks.
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- Hydrogeology Journal, 2019, v. 27, n. 4, p. 1207, doi. 10.1007/s10040-018-01921-w
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Semi-automated filtering of data outliers to improve spatial analysis of piezometric data.
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- Hydrogeology Journal, 2015, v. 23, n. 5, p. 851, doi. 10.1007/s10040-015-1257-y
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- Article
Predictive Assessment of Groundwater Flow Uncertainty in Multiscale Porous Media by Using Truncated Power Variogram Model.
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- Transport in Porous Media, 2019, v. 126, n. 1, p. 97, doi. 10.1007/s11242-018-1071-9
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Geostatistical Simulation and Reconstruction of Porous Media by a Cross-Correlation Function and Integration of Hard and Soft Data.
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- Transport in Porous Media, 2015, v. 107, n. 3, p. 871, doi. 10.1007/s11242-015-0471-3
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- Article
Scale Dependence of Effective Hydraulic Conductivity Distributions in 3D Heterogeneous Media: A Numerical Study.
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- Transport in Porous Media, 2012, v. 94, n. 1, p. 101, doi. 10.1007/s11242-012-9991-2
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- Article
Study of dependence between clay mineral distribution and shale volume in reservoir rocks using geostatistical and petrophysical methods.
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- Geodesy & Cartography, 2015, v. 41, n. 2, p. 92, doi. 10.3846/20296991.2015.1051333
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A GEOSTATISTICAL APPROACH FOR PREDICTING THE TOP PRODUCING FORMATION IN OIL FIELDS.
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- Geodesy & Cartography, 2012, v. 38, n. 3, p. 111, doi. 10.3846/20296991.2012.728896
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On the spatial representativeness of temporal dynamics at European weather stations.
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- International Journal of Climatology, 2014, v. 34, n. 10, p. 3154, doi. 10.1002/joc.3903
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- Article
Nonparametric construction of probability maps under local stationarity.
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- Environmetrics, 2017, v. 28, n. 3, p. 1, doi. 10.1002/env.2438
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- Article