Results 121 to 130 of about 32,193 (219)

Leveraging the TabPFN Algorithm for High‐Resolution Mapping of Groundwater Bicarbonate and Its Scaling Risk Across China

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Large‐scale groundwater quality prediction is often constrained by sparse sampling, limiting the reliability of spatial assessments. This study introduces Tabular Prior‐data Fitted Network (TabPFN), a machine learning model based on prior‐fitting networks, to address this challenge and enable high‐precision mapping of groundwater bicarbonate ...
Tong Sun, Fubin Zhang, Li He, Yanan Tian, Yao Wang, Haochuan Guo, Xiao Liu, Mengxi He, Quanzhou Li   +8 more
wiley   +1 more source

Mapping soil organic carbon in northern France using adaptive zoning regression kriging based on LUCAS dataset

Geocarto International
To improve the accuracy of soil organic carbon (SOC) mapping, an adaptive zoning regression kriging (AZ_RK) framework was proposed, which simultaneously considers spatial heterogeneity and the influence of multiple environmental variables.
Xiaomi Wang, Jiuhong Liu, Yiyun Chen, Leilei Liu, Zihao Wu   +4 more
doaj   +1 more source

Efficiency of Spatial Subsidies Under Information Constraints: A Case Study

Agricultural Economics, Volume 57, Issue 3, May 2026.
ABSTRACT This study compares the efficiency of homogeneous versus spatially heterogeneous subsidies in developing agricultural plans compatible with bird sustainability. Using the plains of Lleida as a case study—where incentives for agricultural intensification threaten a bird community‐we employ a spatially explicit model that simulates crop yields ...
Germán Sánchez‐Arce, Montserrat Viladrich‐Grau   +1 more
wiley   +1 more source

Spatial Modelling of Soil Quality and Lime Requirement for Precision Management in Humid Tropical Coffee Systems

AgriEngineering
Soil heterogeneity and acidity are major constraints to Coffea arabica production in the Amazonian soils of Peru. This study developed a spatial predictive framework that integrates a weighted Soil Quality Index (SQIw) and geostatistical modelling ...
Henry Diaz-Chuquizuta, Sharon Mejia, Ruth Mercado, Michell K. Arroyo-Julca, Ruddy Ore, Percy Diaz-Chuquizuta, Luis Fernando Manrique Gonzales, Martín Sánchez-Ojanasta, Kenyi Quispe   +8 more
doaj   +1 more source

Accurate modeling of antennas using variable-fidelity EM simulations and co-kriging [PDF]

, 2012
Couckuyt, Ivo, Dhaene, Tom, Koziel, Slawomir, Ogurtsov, Stanislav   +3 more
core   +1 more source

Quantifying Uncertainties of Residuals in Symbolic Regression via Kriging

Procedia Computer Science, 2022
Kaifeng Yang, Michael Affenzeller
openaire   +1 more source

Hybrid kriging methods for interpolating sparse river bathymetry point data

Ciência e Agrotecnologia
Terrain models that represent riverbed topography are used for analyzing geomorphologic changes, calculating water storage capacity, and making hydrologic simulations. These models are generated by interpolating bathymetry points.
Pedro Velloso Gomes Batista, Marx Leandro Naves Silva, Fabio Arnaldo Pomar Avalos, Marcelo Silva de Oliveira, Michele Duarte de Menezes, Nilton Curi   +5 more
doaj   +1 more source

PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION

, 2016
In the Gypsum Pole of Araripe, semiarid zone of Pernambuco, where is produces 97% of the plaster consumed in Brazil, a forest experiment with 1875 eucalyptus was cut off and all the trees were rigorously cubed by the Smalian method. The location of each tree was marked on a Cartesian plane, and a sample of 200 trees was removed by entirely random ...
Lundgren, Wellington Jorge Cavalcanti, Silva, José Antônio Aleixo da, Ferreira, Rinaldo Luiz Caraciolo   +2 more
openaire   +1 more source

Monotonicity-Preserving Bootstrapped Kriging Metamodels for Expensive Simulations [PDF]

Kriging (Gaussian process, spatial correlation) metamodels approximate the Input/Output (I/O) functions implied by the underlying simulation models; such metamodels serve sensitivity analysis and optimization, especially for computationally expensive ...
Beers, W.C.M. van, Kleijnen, Jack P.C.
core   +1 more source

Estimating Grassland Carbon Stocks in Hulunber China, Using Landsat8 Oli Imagery and Regression Kriging. [PDF]

Sensors (Basel), 2019
Ding L, Li Z, Wang X, Yan R, Shen B, Chen B, Xin X.   +6 more
europepmc   +1 more source