Results 101 to 110 of about 584,789 (249)
Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction
Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS) positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ...
Ling Huang +5 more
doaj +1 more source
Species richness and diversity in shrub savanna using ordinary kriging
The objective of this work was to analyze the spatial distribution and the behavior of species richness and diversity in a shrub savanna fragment, in 2003 and 2014, using ordinary kriging, in the state of Minas Gerais, Brazil.
A. Batista +5 more
semanticscholar +1 more source
Deep Spatially Varying Coefficient Model for Interpolation of Non‐Stationary Meteorological Data
ABSTRACT In spatial statistics, the spatially varying coefficient model (SVCM) is widely applied in the analysis and interpolation of non‐stationary spatial data. By incorporating spatially varying coefficients, the model can capture spatial heterogeneity and provide an attractive interpretation of response‐covariate associations.
Tong Wu, Nan Chen, Zhi‐Sheng Ye
wiley +1 more source
An Adaptive Moving Window Kriging Based on K-Means Clustering for Spatial Interpolation
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)
Nattakan Supajaidee +2 more
doaj +1 more source
ABSTRACT Compact plate‐fin heat exchangers (PFHEs) are commonly utilized in diverse industries, including aerospace, automotive, processing, and space. Various fin configurations, such as Plain fins, Wavy fins, Lance and Offset fins (OSFs), Perforated fins, louvered fins, and pin fins, are employed in compact heat exchangers (CHEs).
Chennu Ranganayakulu
wiley +1 more source
Bayesian Implementation of the Factor‐Analytic Mixed Model and Application to Embeddings
ABSTRACT Mixed models and neural networks each offer complementary frameworks for prediction. Theoretically grounded in inference, mixed models can unveil latent variance structure notably with the factor‐analytic approach. In this article, we propose to bridge the gap between the two frameworks, leveraging embedding data from a neural network encoder ...
Alexandre Marchal +3 more
wiley +1 more source
ABSTRACT Species distribution models (SDMs) are widely used to predict the spread of invasive species, yet their accuracy over time and the influence of climate data resolution remain unclear. Here, we examine the capacity of SDMs to predict the distribution and short‐term expansion of the invasive gall wasp Dryocosmus kuriphilus, and compare the ...
José Carlos Pérez‐Girón +3 more
wiley +1 more source
In the present study, we used 27 precipitation average monthly data from synoptic, climatologic, rain-guage and evaporative stations located in Zayandeh-Rud river basin for the period of 1970-2014.
M. A. Amini +4 more
doaj
Combining Artificial Neural Network and Ordinary Kriging to Predict Wetland Soil Organic Carbon Concentration in China's Liao River Basin. [PDF]
Kang Y, Li X, Mao D, Wang Z, Liang M.
europepmc +1 more source
ABSTRACT Although numerous prediction methods have been developed, scientific estimation of the spatiotemporal pattern of soil erosion at the watershed scale remains challenging. In this study, fallout radionuclides of 210Pbex and 137Cs were used to estimate average annual soil erosion and deposition in a Mollisol watershed in Northeast China ...
Shaoliang Zhang +7 more
wiley +1 more source

