Results 41 to 50 of about 10,081 (210)

Exponentially‐constrained Gaussian mixture model for quantifying vertical development of water‐conducting fracture zones in lithologically stratified mining roofs

Deep Underground Science and Engineering, EarlyView.
This study proposes an exponentially‐constrained Gaussian mixture model (EcGMM) to quantify vertical fracture heterogeneity in stratified roof strata. The model integrates a piecewise exponential decay term capturing global stress dissipation with Gaussian components representing localized fracture intensification at lithological interfaces.
Huiqing Yuan, Zhimin Xu, Weixiao Chen, Chenghang Zhang, Shijie Xiong, Yajun Sun   +5 more
wiley   +1 more source

Kriging with mixed effects models

Statistica, 2007
In this paper the effectiveness of the use of mixed effects models for estimation and prediction purposes in spatial statistics for continuous data is reviewed in the classical and Bayesian frameworks. A case study on agricultural data is also provided.
POLLICE, Alessio, BILANCIA, Massimo
openaire   +3 more sources

Dynamic prediction of coal and gas outburst risk based on quantitative analysis of stress–energy evolution and adaptive correction

Deep Underground Science and Engineering, EarlyView.
This study quantitatively analyzed the spatiotemporal evolution of stress redistribution ahead of the working face by integrating coal seam distribution, tectonic stress anomalies, gas pressure, and mining‐induced disturbances. An R‐value criterion for coal and gas outburst (CGO) risk assessment was established based on energy principles.
Yingjie Zhao, Xueqiu He, Dazhao Song, Liming Qiu, Minggong Guo, Jie Liu, Qiang Liu, Yi Zhu   +7 more
wiley   +1 more source

Reliability analysis of high-lift device wear based on indicator error control Kriging

Xibei Gongye Daxue Xuebao
To address the issues that the Kriging surrogate model using the learning function as the convergence criterion cannot reflect the accuracy of predicted failure probability directly and accurately and incur high computational cost in modeling, a ...
FENG Yunwen, ZHOU Sirui, XUE Xiaofeng, CHEN Junyu, CAO Jinfan, CHEN Xianmin, GE Jianbing   +6 more
doaj   +1 more source

Development of automatic charging control optimization technique for continuous-type inkjet printers using charged-droplet flight simulation and Bayesian optimization

Nihon Kikai Gakkai ronbunshu, 2022
Conventionally, repeated experiments by trial and error have been used to improve the printing quality of continuous-type inkjet printers. This is because the trajectories of the ink droplets are affected by external forces such as air drag and Coulomb ...
Koma SATO, Eiji ISHII, Shoichiro KISANUKI, Tsuneaki TAKAGISHI, Manabu KATO   +4 more
doaj   +1 more source

Human pressure, habitat heterogeneity and species traits jointly determine the level of dark diversity in coastal fish communities

Ecography, EarlyView.
Understanding how anthropogenic pressures and environmental gradients shape coastal fish communities is a central question in biogeography and marine conservation. Yet, the set of species expected to occur at a site given ecological conditions but being absent – the so‐called dark diversity – has received far less attention than observed species, even ...
Loïc Sanchez, Jeanne Rolland, Adèle Barroil, Célia Bertrand, Agathe Blandin, Pierre Boissery, Thomas Bockel, Eric Charbonnel, Julie Deter, Régis Hocdé, Florian Holon, Jean‐Baptiste Juhel, Nicolas Loiseau, Bastien Macé, Anthony Maire, Stéphanie Manel, Marie Orblin, Franck Pichot, Jean‐Jacques Riutort, Lola Romant, Rémy Simide, Alice Valentini, Laure Velez, David Mouillot   +23 more
wiley   +1 more source

Application of a semivariogram based on a deep neural network to Ordinary Kriging interpolation of elevation data.

PLoS ONE, 2022
The Ordinary Kriging method is a common spatial interpolation algorithm in geostatistics. Because the semivariogram required for kriging interpolation greatly influences this process, optimal fitting of the semivariogram is of major significance for ...
Yang Li, Zhong Baorong, Xu Xiaohong, Liang Zijun   +3 more
doaj   +1 more source

Beyond Prediction: Data, Baselines, Explanation, and Causation in Machine Learning for Food Insecurity

Food Safety and Health, EarlyView.
The gains from machine learning in nowcasting and forecasting food insecurity are still small and limited and cannot be observed in all countries. This review summarizes the public resources for data, corrects common misconceptions about model requirements, and establishes baseline requirements, explanations, causal inference, and equity in operational
Shabnam Mehboob, Azman Abdullah, Gunesh Kumar, Samreen Memon, Naila Afghan   +4 more
wiley   +1 more source

Statistical Downscaling of Daily Temperature and Precipitation From Regional Climate Models in Complex Mountain Terrain

International Journal of Climatology, EarlyView.
The study provides insights for post‐processing climate model output in complex terrain, useful for climate change impact models. We compared different bias adjustment and downscaling techniques from quantile delta mapping to simple lapse rates. We developed a new spatial downscaling method based on principal components analysis, which showed superior ...
Michael Matiu, Anna Napoli, Alberto Bellin, Dino Zardi, Bruno Majone   +4 more
wiley   +1 more source

Kriging Numerical Models for Geotechnical Reliability Analysis

Soils and Foundations, 2011
When the performance function is an implicit numerical model, geotechnical reliability analysis can be challenging due to the coupling between the deterministic numerical evaluation and reliability analysis. Previously, the kriging method was used in geotechnical engineering for modeling the spatial variability of soil properties.
ZHANG, J., ZHANG, L. M., TANG, WILSON H.
openaire   +2 more sources