|
|
|
Nattakan Supajaidee, Nawinda Chutsagulprom and Sompop Moonchai
Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AMWKK)...
ver más
|
|
|
|
|
|
|
Abdelkrim Lachgar, David J. Mulla and Viacheslav Adamchuk
One of the challenges in site-specific phosphorus (P) management is the substantial spatial variability in plant available P across fields. To overcome this barrier, emerging sensing, data fusion, and spatial predictive modeling approaches are needed to ...
ver más
|
|
|
|
|
|
|
Hosang Han and Jangwon Suh
The accurate prediction of soil contamination in abandoned mining areas is necessary to address their environmental risks. This study employed a combined model of machine learning and geostatistics to predict the spatial distribution of soil contaminatio...
ver más
|
|
|
|
|
|
|
Vinh Pham, Maxim Tyan, Tuan Anh Nguyen and Jae-Woo Lee
Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity...
ver más
|
|
|
|
|
|
|
Thiago dos Santos Gonçalves, Harald Klammler and Luíz Rogério Bastos Leal
Aquifer properties, such as hydraulic transmissivity T and its spatial variability, are fundamental for sustainable groundwater exploitation in arid regions. Especially in karst aquifers, spatial variability can be considerable, and the application of ge...
ver más
|
|
|
|
|
|
|
Anthony A. Amori, Olufemi P. Abimbola, Trenton E. Franz, Daran Rudnick, Javed Iqbal and Haishun Yang
Model calibration is essential for acceptable model performance and applications. The Hybrid-Maize model, developed at the University of Nebraska-Lincoln, is a process-based crop simulation model that simulates maize growth as a function of crop and fiel...
ver más
|
|
|
|
|
|
|
Saile Zhang, Qingzhen Yang, Rui Wang and Xufei Wang
The use of traditional optimization methods in engineering design problems, specifically in aerodynamic and infrared stealth optimization for engine nozzles, requires a large number of objective function evaluations, therefore introducing a considerable ...
ver más
|
|
|
|
|
|
|
Chunyun Shen, Jiahao Zhang, Chenglin Ding and Shiming Wang
By combining computational fluid dynamics (CFD) and surrogate model method (SMM), the relationship between turbine performance and airfoil shape and flow characteristics at low flow rate is revealed. In this paper, the flow velocity tidal energy airfoil ...
ver más
|
|
|
|
|
|
|
Yuyin Chen, Yongqiang Zhang, Jing Tian, Zixuan Tang, Longhao Wang and Xuening Yang
As extreme climate events become more common with global warming, groundwater is increasingly vital for combating long-term drought and ensuring socio-economic and ecological stability. Currently, the mechanism of meteorological drought propagation to gr...
ver más
|
|
|
|
|
|
|
Pierre Goovaerts, Thomas Hermans, Peter F. Goossens and Ellen Van De Vijver
This paper addresses two common challenges in analyzing spatial epidemiological data, specifically disease incidence rates recorded over small areas: filtering noise caused by small local population sizes and deriving estimates at different spatial scale...
ver más
|
|
|
|