Results 41 to 50 of about 4,853,850 (241)

XCO₂ Fusion Algorithm Based on Multi-Source Greenhouse Gas Satellites and CarbonTracker

Atmosphere, 2023
In view of the urgent need for high coverage and high-resolution atmospheric CO2 data in the study of carbon neutralization and global CO2 change research, this study combines the Kriging interpolation and the Triple Collision (TC) algorithm to fuse ...
Ailin Liang, Ruonan Pang, Cheng Chen, Chengzhi Xiang   +3 more
doaj   +1 more source

A Novel Combination Co-Kriging Model Based on Gaussian Random Process

Mathematical Problems in Engineering, 2018
Co-Kriging (CK) modeling provides an efficient way to predict responses of complicated engineering problems based on a set of sample data obtained by methods with varying degree of accuracy and computation cost. In this work, the Gaussian random process (GRP) is introduced to construct a novel combination CK model (CK-GRP) to improve the prediction ...
Huan Xie, Wei Zeng, Hong Song, Wen Sun, Tao Ren   +4 more
openaire   +1 more source

OPTIMIZATION OF MULTI-FIDELITY DATA USING CO-KRIGING FOR HIGH DIMENSIONAL PROBLEMS [PDF]

The International Conference on Applied Mechanics and Mechanical Engineering, 2014
ABSTRACTThis paper deals with an efficient and multi-fidelity design strategy for high dimensional industrial problems. The most significant factors have been determined based on the Muschelknautz method of modeling (MM) using the screening approach. For cyclone separator, only four (from seven) geometrical parameters are significant.
Elsayed, Khairy, Lacor, Christian
openaire   +2 more sources

Revolutionising Agricultural Sustainability: New ‘Furrow Tillage’ can Mitigate Short‐Term Soil‐to‐Atmosphere CO2 Flux and Promote Soil‐Plant‐Microbe Health

Advanced Science, EarlyView.
Furrow tillage resolves the conventional‐vs.‐no‐tillage trade‐off by simultaneously cutting CO2 efflux to 2.0–3.0 g C m−2 d−1 and unlocking high nutrient availability for the rice rhizosphere. This scalable agronomic solution strengthens soil health, enhances plant physiology, reshapes microbial metabolism, and shifts paddy systems toward a net ...
Arnab Majumdar, Munish Kumar Upadhyay, Argha Ghosh, Rakesh Biswas, Ioly Kotta Loizou, Martin Buck, Mark Tibbett, Biswajit Giri, Debojyoti Moulick, Manoj Kumar Jaiswal, Tarit Roychowdhury   +10 more
wiley   +1 more source

A Novel Wind-Aware Dynamic Graph Neural Network for Urban Ground-Level Ozone Concentration Prediction

ISPRS International Journal of Geo-Information
Ground-level ozone pollution poses significant risks to public health and ecosystems and remains a major environmental challenge worldwide. Accurate forecasting is difficult due to the nonlinear formation mechanisms of ozone and its strong dependence on ...
Wenjie Wu, Xinyue Mo, Huan Li
doaj   +1 more source

Failure Probability Assessment using co-Kriging Surrogate Models

Procedia Engineering, 2015
Abstract Industries, among them the aeronautics industry, have to justify the reliability of the structures they design. Static and modal analyzes are the classical methods to validate designs. Nowadays, these are not sufficient anymore, and the damage tolerance approaches, characterizing the severity of a flaw occurring in the designed assembly, are
Lefebvre, J.-P., Dompierre, B., Robert, A., Le Bihan, M., Wyart, E., Sainvitu, C.   +5 more
openaire   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
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, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

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

Digital Mapping of Soil Texture Particles with Machine Learning Models and Environmental Covariates [PDF]

مجله آب و خاک
IntroductionUnderstanding the particle size distribution (PSD) is of great importance for plant growth and soil management. In recent years, the science of soil has witnessed a significant increase in digital soil mapping (DSM) activities. In this regard,
P. Khosravani, M. Baghernejad, A.A. Moosavi, S.R. Fallah Shamsi   +3 more
doaj   +1 more source

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