Results 131 to 140 of about 538,368 (282)

Revealing Dust Source Changes in East Asia From Past to Future: An Interpretable Deep Learning Approach

Land Degradation &Development, EarlyView.
ABSTRACT Aeolian dust source areas are controlled by climate and human activities and are closely associated with land degradation, yet their long‐term evolution under global warming remains insufficiently quantified. An integrated framework that couples a U‐Net segmentation model with Shapley Additive Explanations (SHAP) was built to map and attribute
Yanyu Li, Qizhong Wu, Xueshun Chen, Jiang Yue, Jieying He, Huaqiong Cheng   +5 more
wiley   +1 more source

From experience of using mechatronics subsystems in rectification technology [PDF]

, 2016
Authors suggest the energy saving technology of the rectification with controllable cycles of delay and overflowing of liquid without interrupting of steam and liquid flows supply in the column due to additionally installed valves on the moving rods ...
Shiyan, Peter, Bulii, Yurii, Kuts, Anatoly   +2 more
core  

Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch

Naval Research Logistics (NRL), EarlyView.
ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley   +1 more source

Learning from mistakes: Understanding and refining machine learning predictions of extinction risk for single‐country endemics

PLANTS, PEOPLE, PLANET, EarlyView.
As of 2026, fewer than 23% of vascular plants have IUCN Red List assessments, despite accelerating threats to biodiversity. Predictive models of extinction risk complement assessments and help prioritize conservation action but face a trade‐off between data resolution and species coverage.
Emma S. Ericksen, Steven P. Bachman, Amy Barker, James S. Borrell, Andrew P. Budden, Shambel Alemu Chengere, Iain Darbyshire, Becca Davis, Kelda F. V. A. Elliott, Tesfanesh Feseha, Bezawit Genanaw, Hanny Lidetu, Lidet Mehari, Efrata Mekebib, Henry Miller, Timothy R. Pearce, Jack F. Plummer, Alexandra Roberts, Harry Smith, Emily Terry, Carolina Tovar, Jenna C. Willis, Sebsebe Demissew, Ermias Lulekal, Sileshi Nemomissa, Vida J. Svahnström, Eimear Nic Lughadha, Matilda J. M. Brown   +27 more
wiley   +1 more source

Object‐based deep learning for probabilistic convective‐core nowcasting from satellite data

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Convective cores detected from Meteosat infrared imagery are represented as compact physical objects to generate probabilistic nowcasts up to 6 h ahead. A spatio‐temporal transformer models interactions among evolving core populations and produces gridded probability forecasts across the western Sahel.
Mendrika Rakotomanga, Douglas J. Parker, Nadhir Ben Rached, Seonaid R. Anderson, Cornelia Klein, Steven C. Wells   +5 more
wiley   +1 more source

Balancing accuracy and speed: A multi‐fidelity ensemble Kalman filter with a machine learning surrogate model

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We investigate the use of a multi‐fidelity ensemble Kalman filter (EnKF) in which the low‐fidelity model is a machine‐learning model, instead of a traditional low‐resolution model. Results with the Lorenz‐2005 and quasi‐geostrophic models show that we can achieve improved accuracy within the same computational budget compared with the standard EnKF ...
Jeffrey van der Voort, Martin Verlaan, Hanne Kekkonen   +2 more
wiley   +1 more source

Efficiency increasing of Kuibyshevski refinery gas fractionation unit due to replacement of fractionation absorber to rectification column.

Тонкие химические технологии, 2007
The efficiency comparative analysis was carried out for fractionation absorber and rectification columns for feed deethanization at the Kuibyshevski Refinery gas fractionation unit for power inputs ...
M. L. Golovanov, A. V. Oskirko, A. V. Timoshenko, E. N. Voronov   +3 more
doaj  

Toward Encrypted OPF Across Transmission and Distribution—Prospects and Open Problems of Encrypted Quadratic Programming

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT The increasing integration of distributed energy resources demands enhanced coordination between transmission system operators (TSOs) and distribution system operators (DSOs) to maintain reliable grid operation. Traditional approaches rely on hierarchical or distributed optimization schemes for power flow management, but these methods either ...
Janis Adamek, Philipp Binfet, Maísa Beraldo Bandeira, Timm Faulwasser, Moritz Schulze Darup   +4 more
wiley   +1 more source

Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño, Alejandro Palacio‐Betancur, Piedad Miranda‐Chiquito, Juan David Amaya, Christian E. Silva, Mariantonieta Gutierrez Soto, Luis Felipe Giraldo   +6 more
wiley   +1 more source

Propylene-Propane Rectification Column's Examination

MultiScience - XXXIII. microCAD International Multidisciplinary Scientific Conference, 2019
Viktória Kállai, Gábor L. Szepesi, Péter Mizsey   +2 more
openaire   +1 more source