Results 51 to 60 of about 37,239 (228)
Spatial Interpolation of Geotechnical Properties Using EBK, IDW, and Kriging: A Case Study in Astana, Kazakhstan [PDF]
This paper investigates the performance of interpolation methods for defining intermediate geotechnical soil properties, such as Empirical Bayesian Kriging (EBK), Inverse Distance Weighting (IDW), and ordinary Kriging.
Mukhamejanova Assel +4 more
doaj +1 more source
Fluid flow through a single fracture is commonly described by the cubic law. However, deviations from this model are expected because natural fracture surfaces are rough and in contact with each other in discrete regions. In this study, the interactions between fracture closure, contact area, and hydraulic characterization of mesoscopic‐scale rough ...
Chenghao Han +5 more
wiley +1 more source
Based on Open CASCADE and Ordinary Kriging interpolation algorithm, a software development framework adding geostatistical interpolation algorithm to CAD geometry operation core for three-dimensional hydrogeological modeling is designed.
LI Peng, JIN Dewu, CHENG Jianyuan, ZHAO Chunhu
doaj +1 more source
Multi-objective design of antenna structures using variable-fidelity EM simulations and co-kriging [PDF]
A methodology for low-cost multi-objective design of antenna structures is proposed. To reduce the computational effort of the design process the initial Pareto front is obtained by optimizing the response surface approximation (RSA) model obtained from ...
Couckuyt, Ivo +3 more
core +1 more source
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza +4 more
wiley +1 more source
A generative deep neural network as an alternative to co-kriging
In geosciences, kriging is leading spatial interpolation, and co-kriging is the most commonly used method for accomplishing spatial interpolation of a target variable by incorporating information from a secondary variable.
Herbert Rakotonirina +3 more
doaj +1 more source
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li +4 more
wiley +1 more source
Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium [PDF]
Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging) are widely applied in spatial interpolation from point measurement to continuous surfaces.
S. Ly, C. Charles, A. Degré
doaj +1 more source
Sunshine Duration in Brazil From Meteosat (1983–2020): Climatology, Variability and Long‐Term Trends
Using nearly four decades of Meteosat satellite data (1983–2020), this study presents a country‐wide climatology of sunshine duration (SDU) in Brazil. The results reveal marked regional contrasts, dominant modes of variability, and significant long‐term trends, providing new information on the most relevant meteorological systems that influence SDU and
Maria Lívia Lins Mattos Gava +2 more
wiley +1 more source
Spatial characteristics of thunderstorm rainfall fields and their relation to runoff [PDF]
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

