Results 31 to 40 of about 1,727,853 (256)
SwinLSTM:Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM
, 2023 Integrating CNNs and RNNs to capture spatiotemporal dependencies is a prevalent strategy for spatiotemporal prediction tasks. However, the property of CNNs to learn local spatial information decreases their efficiency in capturing spatiotemporal ...
Tang, RongNian +3 more
core
A Spatiotemporal Coupling Calculation-Based Short-Term Wind Farm Cluster Power Prediction Method
IEEE Access, 2023 Accurate short-term wind power prediction is of great significance to the real-time dispatching of power systems and the development of wind power generation plans.
Haochen Li, Liqun Liu, Qiusheng He
doaj +1 more source
Characterizing Cutaneous α‐Synuclein Deposition and Seeding Activity in Parkinson's Disease Subtypes
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Cutaneous phosphorylated α‐synuclein (p‐syn) and α‐synuclein seeding activity are promising biomarkers for Parkinson's disease (PD), but their clinical value remains uncertain due to disease heterogeneity. This study evaluates these two biomarkers in PD patients to inform phenotype‐specific diagnosis and disease severity assessment ...
Yuting Jin +8 more
wiley +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Spatiotemporal Model Based on Deep Learning for ENSO Forecasts
Atmosphere, 2021 El Niño and Southern Oscillation (ENSO) is closely related to a series of regional extreme climates, so robust long-term forecasting is of great significance for reducing economic losses caused by natural disasters.
Huantong Geng, Tianlei Wang
doaj +1 more source
A refined maximum predictability for next location prediction with fusion knowledge.
PLoS ONEResearch on maximum predictability for next location prediction aims to derive the theoretical maximum accuracy that an ideal prediction model could achieve, which is crucial for analyzing travel regularity and evaluating prediction models.
Liuhong Huang +3 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling +15 more
wiley +1 more source
Fire, 2023 Fire spread prediction is a crucial technology for fighting forest fires. Most existing fire spread models focus on making predictions after a specific time, and their predicted performance decreases rapidly in continuous prediction due to error ...
Xinyu Wang +8 more
doaj +1 more source
How to control the spatiotemporal spread of Omicron in the region with low vaccination rates
Frontiers in Public Health, 2022 Currently, finding ways to effectively control the spread of Omicron in regions with low vaccination rates is an urgent issue. In this study, we use a district-level model for predicting the COVID-19 symptom onset risk to explore and control the whole ...
Chengzhuo Tong +3 more
doaj +1 more source
Advanced Functional Materials, EarlyView.A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao +6 more
wiley +1 more source