Results 181 to 190 of about 5,207,763 (284)

MEMS Gyroscope Temperature Compensation Based on Improved Complete Ensemble Empirical Mode Decomposition and Optimized Extreme Learning Machine. [PDF]

Micromachines (Basel)
Zhang Z, Zhang J, Zhu X, Ren Y, Yu J, Cao H.   +5 more
europepmc   +1 more source

A Novel Hybrid Approach for Partial Discharge Signal Detection Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Approximate Entropy. [PDF]

Entropy (Basel), 2020
Shang H, Li Y, Xu J, Qi B, Yin J.
europepmc   +1 more source

Data‐Driven Prediction of Block Copolymer Morphology Using Coarse‐Grained Modeling and Machine Learning

Journal of Polymer Science, EarlyView.
An integrated framework combining high‐throughput CG‐MD simulations, automated image‐based feature extraction, and supervised machine learning enables efficient, interpretable, and data‐driven prediction of block copolymer morphological behaviors.
Lan Xu, Zhaofan Li, Wenjie Xia
wiley   +1 more source

Forecasting of the true satellite carbon monoxide data with ensemble empirical mode decomposition, singular value decomposition and moving average. [PDF]

J Appl Stat
Poongadan S, Lineesh MC.
europepmc   +1 more source

The benefit of neighborhood methods for the assimilation of cloud‐affected radiances evaluated in observing‐system simulation experiments

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Neighborhood methods are commonly used in verification to avoid the double‐penalty issue. This study evaluates such methods for the assimilation of infrared and visible satellite observations and extends them to multiscale assimilation. Moreover, a novel technique is tested aimed at mitigating complex biases and structural errors in real‐world model ...
Lukas Kugler, Stefano Serafin, Andrea Hochebner, Nicola Pierotti, Martin Weissmann   +4 more
wiley   +1 more source

Beyond Frequency Bands: Complementary-Ensemble-Empirical-Mode-Decomposition-Enhanced Microstate Sequence Non-Randomness Analysis for Aiding Diagnosis and Cognitive Prediction of Dementia. [PDF]

Brain Sci
Wan W, Gu Z, Peng CK, Cui X.
europepmc   +1 more source

Mode mixing problem in empirical mode decomposition

, 2018
Deneysel Mod Ayrıştırması (EMD), bir çok alanda doğrusal olmayan ve durağan olmayan zaman serisi verilerini analiz etmek için özellikle son yıllarda yaygın olarak kullanılmıştır.
MUHAMMED I JAITEH
core  

Evaluation of a stochastically perturbed parametrisations scheme for sea ice in sub‐seasonal forecasts

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Overconfident sea ice forecasts pose a challenge in subseasonal prediction. To test a potential way to address this issue and account for sea ice model uncertainty, this article investigates a stochastically perturbed parametrisations (SPP) scheme for sea ice in a prototype CY49R2 configuration of the coupled IFS‐NEMO4‐SI3 system. The results show that
Jonas Spaeth, Steffen Tietsche, Kristian Strommen, Michael Mayer, Andrea Storto, Christopher D. Roberts, Sarah‐Jane Lock, Sarah Keeley   +7 more
wiley   +1 more source

Calibration of medium‐range temperature ensemble forecasts dependent on the time horizon: An assessment

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Numerical weather prediction output necessitates calibration, as weather model systems are unable to replicate the correct statistics of observations. Such processing is especially important when predicting extreme weather. Calibration methods function by learning from prediction inadequacies during a training phase and by exploiting this information ...
Dmitrij Japs, Oleksiy Boyko, Paolo Reggiani, Ezio Todini   +3 more
wiley   +1 more source

Early Detection of Sudden Cardiac Death by Using Ensemble Empirical Mode Decomposition-Based Entropy and Classical Linear Features From Heart Rate Variability Signals. [PDF]

Front Physiol, 2020
Shi M, He H, Geng W, Wu R, Zhan C, Jin Y, Zhu F, Ren S, Shen B.   +8 more
europepmc   +1 more source