Application of Fast MEEMD–ConvLSTM in Sea Surface Temperature Predictions
Remote SensingSea Surface Temperature (SST) is of great importance to study several major phenomena due to ocean interactions with other earth systems. Previous studies on SST based on statistical inference methods were less accurate for longer prediction lengths.
R. W. W. M. U. P. Wanigasekara +4 more
doaj +2 more sources
Unravelling Diurnal Asymmetry of Surface Temperature in Different Climate Zones [PDF]
Scientific Reports, 2017 Understanding the evolution of Diurnal Temperature Range (DTR), which has contradicting global and regional trends, is crucial because it influences environmental and human health.
R. Vinnarasi +3 more
doaj +2 more sources
Climate change heterogeneity: A new quantitative approach. [PDF]
PLoS OneClimate change is a spatial and temporarily non-uniform phenomenon that requires understanding its evolution to better evaluate its potential societal and economic impact.
Rivas MDG, Gonzalo J.
europepmc +4 more sources
Fault Diagnosis of Rolling Bearing based on MEEMD-DHENN
Jixie chuandong, 2018 According to the non-stationary and nonlinearity of the fault signals from rolling bearing,a recognition method based on Modified Ensemble Empirical Mode Decomposition（ MEEMD） and Double Hiddenlayer Elman Neural Network（ DHENN） is proposed. The vibration
Wang Jinrui +3 more
doaj +1 more source
"Good and bad investments" in public health stocks amid the COVID-19 shock: evidence from a transformer-based model. [PDF]
Front Public HealthIntroductionMajor public health emergencies have profoundly reshaped the risk structure and resource allocation logic of capital markets. The market performance of public health-related enterprises has exhibited substantial heterogeneity across different
Zhao D, Li Y, Gu R.
europepmc +3 more sources
ERTNet: an interpretable transformer-based framework for EEG emotion recognition. [PDF]
Front NeurosciBackgroundEmotion recognition using EEG signals enables clinicians to assess patients’ emotional states with precision and immediacy. However, the complexity of EEG signal data poses challenges for traditional recognition methods.
Liu R +6 more
europepmc +3 more sources
Applied SciencesComparing the empirical modal decomposition (EMD) method and the modified ensemble empirical modal decomposition (MEEMD) method, a response analysis of the long-period components, with the separation and reconstruction of the two methods, and the ...
Chunyu Li, Jingwei Jia, Jie Jia
doaj +2 more sources
Recent Advances in Active Infrared Thermography for Non-Destructive Testing of Aerospace Components. [PDF]
Sensors (Basel), 2018 Active infrared thermography is a fast and accurate non-destructive evaluation technique that is of particular relevance to the aerospace industry for the inspection of aircraft and helicopters’ primary and secondary structures, aero-engine parts ...
Ciampa F, Mahmoodi P, Pinto F, Meo M.
europepmc +5 more sources
MEEMD Decomposition-Prediction-Reconstruction Model of Precipitation [PDF]
, 2022 Abstract Aiming at the low prediction accuracy of precipitation time series data, proposes an Modified Ensemble Empirical Mode Decomposition-prediction-reconstruction model（MDPRM）. First,The non-stationary precipitation time series is decomposed into multiple decomposition terms by MEEMD.
Yongtao Wang +4 more
openaire +1 more source
A VMD and LSTM based hybrid model of load forecasting for power grid security [PDF]
, 2022 As the basis for the static security of the power grid, power load forecasting directly affects the safety of grid operation, the rationality of grid planning, and the economy of supply-demand balance.
Lv, Lingling +5 more
core +2 more sources