Results 71 to 80 of about 32,193 (219)

Structural Optimization of 3D Braided Tungsten–Copper Composites via Active Learning and Finite Element Simulation

Materials Genome Engineering Advances, EarlyView.
An uncertainty‐aware FEM–GPR active learning framework efficiently explores the design space of 3D braided W–Cu composites, identifying architectures with higher yield strength and preserved electrical conductivity, whereas SHAP interpretation highlights yarn spacing in the braid plane as the key structural factor controlling composite performance ...
Lai Zhang, Tianwen Chen, Yongjing Wu, Fuzhu Liu, Yaping Wang, Zhimao Yang, Shengchun Yang   +6 more
wiley   +1 more source

A new method to identify and explain sources of precipitation modification, illustrated for the western Netherlands

Quarterly Journal of the Royal Meteorological Society, EarlyView.
This study develops a method to identify the source areas of precipitation events, as illustrated for the western part of the Netherlands. Radar‐based precipitation data are traced back to their source areas and machine‐learning techniques are used to identify hypothesized causes: urban heat, surface roughness, and air pollution. We find that urban and
Jelmer van der Graaff, Gert‐Jan Steeneveld   +1 more
wiley   +1 more source

Spatial distribution of soil organic carbon and total nitrogen based on GIS and geostatistics in a small watershed in a hilly area of northern China.

PLoS ONE, 2013
The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed
Gao Peng, Wang Bing, Geng Guangpo, Zhang Guangcan   +3 more
doaj   +1 more source

A Machine Learning Technique for Spatial Interpolation of Solar Radiation Observations

Earth and Space Science, 2021
This study applies statistical methods to interpolate missing values in a data set of radiative energy fluxes at the surface of Earth. We apply Random Forest (RF) and seven other conventional spatial interpolation models to a global Surface Solar ...
Thomas Leirvik, Menghan Yuan
doaj   +1 more source

Above-Ground Biomass Estimation for Coniferous Forests in Northern China Using Regression Kriging and Landsat 9 Images

Remote Sensing, 2022
Accurate estimation of forest above-ground biomass (AGB) is critical for assessing forest quality and carbon stocks, which can improve understanding of the vegetation growth processes and the global carbon cycle.
Fugen Jiang, Hua Sun, Erxue Chen, Tianhong Wang, Yaling Cao, Qingwang Liu   +5 more
doaj   +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, Myers, DE, Sorooshian, S, Syed, KH   +3 more
core   +1 more source

Kriging prior regression: A case for kriging-based spatial features with TabPFN in soil mapping

Computers and Electronics in Agriculture
Machine learning and geostatistics are two fundamentally different frameworks for predicting and spatially mapping soil properties. Geostatistics leverages the spatial structure of soil properties, while machine learning captures the relationship between available environmental features and soil properties.
Schmidinger, Jonas, Barkov, Viacheslav, Vogel, Sebastian, Atzmueller, Martin, Heuvelink, Gerard B.M.   +4 more
openaire   +2 more sources

Epistemic and aleatoric uncertainty quantification in weather and climate models

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Aleatoric and epistemic uncertainties over time on weather and climate time‐scales, estimated through ensembles that sample aleatoric and epistemic uncertainty using Bayesian neural networks for parameterisations in the Lorenz 1996 model. The spread shows the 16th and 84th percentiles.
Laura A. Mansfield, Hannah M. Christensen   +1 more
wiley   +1 more source

Accessing the spatial distribution of aboveground biomass in tropical mountain forests using regression kriging simulation: a geostatistical approach for local-scale estimates

Ecological Processes
Background Accurate measurements of aboveground biomass (AGB) are essential for understanding the planet’s carbon balance. The Atlantic Forest of the Serra do Mar in southeastern Brazil contains large areas of well-preserved remnants, characterized by ...
Joel Carlos Rodrigues Otaviano, Cássio Freitas Pereira de Almeida   +1 more
doaj   +1 more source

Using NDVI and guided sampling to develop yield prediction maps of processing tomato crop

Spanish Journal of Agricultural Research, 2015
The use of yield prediction maps is an important tool for the delineation of within-field management zones. Vegetation indices based on crop reflectance are of potential use in the attainment of this objective.
Rafael Fortes, María H. Prieto, Abelardo García-Martín, Antón Córdoba, Carlos Campillo   +4 more
doaj   +1 more source