Results 91 to 100 of about 77,394 (227)
Advances in Kriging-Based Autonomous X-Ray Scattering Experiments. [PDF]
, 2020 Autonomous experimentation is an emerging paradigm for scientific discovery, wherein measurement instruments are augmented with decision-making algorithms, allowing them to autonomously explore parameter spaces of interest.
Doerk, Gregory S +4 more
core
DCENT‐I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset
Geoscience Data Journal, Volume 13, Issue 2, April 2026.DCENT‐I infills data gaps in DCENT, producing spatially coherent temperature fields (top) and a slightly higher GMST warming estimate (bottom). Top: December 1877 temperature anomalies (°C; 1961–1990 December baseline) from DCENT (left) and DCENT‐I (right). Bottom: GMST before (DCENT, blue) and after (DCENT‐I, red) infilling.
Duo Chan +8 more
wiley +1 more source
Spatial characteristics of thunderstorm rainfall fields and their relation to runoff [PDF]
, 2003 The main aim of this study was to assess the ability of simple geometric measures of thunderstorm rainfall in explaining the runoff response from the watershed. For calculation of storm geometric properties (e.g.
Goodrich, DC +3 more
core +1 more source
Digital mapping of soil erodibility: A case study of the Ravang watershed, southern Iran
Agrosystems, Geosciences &Environment, Volume 9, Issue 1, March 2026.Abstract The Universal Soil Loss Equation incorporates soil erodibility as a key parameter for erosion quantification. This study focused on mapping soil erodibility patterns and identifying the primary factors influencing its spatial distribution within the Ravang watershed, located in southern Iran's Hormozgan Province.
Fahimeh Torkamani +3 more
wiley +1 more source
Expected Improvement in Efficient Global Optimization Through Bootstrapped Kriging - Replaces CentER DP 2010-62 [PDF]
This article uses a sequentialized experimental design to select simulation input com- binations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output ...
Beers, W.C.M. van +2 more
core +1 more source
A Bayesian Spatiotemporal Functional Model for Data With Block Structure and Repeated Measures
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT The analysis of spatiotemporal data is fundamental across multiple scientific disciplines, particularly in assessing the behavior of climate effects over space and time. A key challenge in this area is effectively capturing recurring climate phenomena, such as El Niño/La Niña (ENSO) phases, which induce prolonged periods of similar weather ...
David H. da Matta +3 more
wiley +1 more source
Post-processing Kriging with External Drift Estimates [PDF]
Geologia USP. Série Científica, 2009 Kriging with an external drift has been used for estimating a poorly sampled variable based on an exhaustively sampledsecondary variable. Even considering the information coming from secondary data, the estimates present smaller variancethan the sample ...
Jorge Kazuo Yamamoto
doaj
Jurnal Matematika Integratif, 2015 Geostatistika merupakan perpaduan ilmu pertambangan, geologi, matematika, dan statistika. Data yang digunakan dalam geostatistika merupakan data spasial yakni nilai pengamatan berdasarkan lokasi.
Annisa Nur Falah +2 more
doaj +1 more source
Bayesian Inference for Spatially‐Temporally Misaligned Data Using Predictive Stacking
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT Air pollution remains a major environmental risk factor that is often associated with adverse health outcomes. However, quantifying and evaluating its effects on human health is challenging due to the complex nature of exposure data. Recent technological advances have led to the collection of various indicators of air pollution at increasingly
Soumyakanti Pan, Sudipto Banerjee
wiley +1 more source
Evolutionary model type selection for global surrogate modeling [PDF]
, 2009 Due to the scale and computational complexity of currently used simulation codes, global surrogate (metamodels) models have become indispensable tools for exploring and understanding the design space.
De Turck, Filip +2 more
core +1 more source