Results 41 to 50 of about 8,576 (212)

Multimode Decomposition and Wavelet Threshold Denoising of Mold Level Based on Mutual Information Entropy

Entropy, 2019
The continuous casting process is a continuous, complex phase transition process. The noise components of the continuous casting process are complex, the model is difficult to establish, and it is difficult to separate the noise and clear signals ...
Zhufeng Lei, Wenbin Su, Qiao Hu
doaj   +1 more source

Forecasting Daily Flood Water Level Using Hybrid Advanced Machine Learning Based Time-Varying Filtered Empirical Mode Decomposition Approach [PDF]

, 2022
Accurate water level forecasting is important to understand and provide an early warning of food risk and discharge. It is also crucial for many plants and animal species that needs specific ranges of water level. This research focused on long term multi-
Mehdi Jamei, Yaseen, Zaher Mundher, Shahab Abdulla, Prasad, Ramendra, Malik, Anurag, Abdulla, Shahab, Ali, Mumtaz, Anurag Malik, Ramendra Prasad, Mumtaz Ali, Jamei, Mehdi, Zaher Mundher Yaseen   +11 more
core   +1 more source

Development of Empirical Mode Decomposition [PDF]

, 2020
In this paper, one of the tasks for which empirical mode decomposition is potentially useful is nonparametric signal denoising, an area for which wavelet thresholding has been the dominant technique for many years. In this paper, the wavelet thresholding
Nayak, R. samba Siva
core   +2 more sources

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

Advanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su, Yanda Zhu, Hao Peng, Manman Li, Xuzihan Zhang, Meixiao Wu, Siyuan Zhang, Yuhan Zeng, Jiwen Liao, Ming Luo, Hetaishan Huang, Yutong Wang, Sean Li, Wenxian Li   +13 more
wiley   +1 more source

Pressure fluctuation signal analysis of pump based on ensemble empirical mode decomposition method

Water Science and Engineering, 2014
Pressure fluctuations, which are inevitable in the operation of pumps, have a strong non-stationary characteristic and contain a great deal of important information representing the operation conditions.
Hong Pan, Min-sheng Bu
doaj   +1 more source

Variance‐Empirical Mode Decomposition Method for Fault Detection in MMC‐HVDC Transmission Lines

Energy Science &Engineering, EarlyView.
A variance‐embedded empirical mode decomposition (VEMD) method is proposed for fast and accurate fault detection in MMC‐HVDC transmission lines. By combining variance analysis with EMD, the method reliably detects various faults without communication links and remains robust to noise and non‐fault transients.
Seyed Amir Hosseini, Behrooz Taheri
wiley   +1 more source

Monitoring and assessment for obstructive sleep apnea

FlexMat, EarlyView.
This review systematically classifies Obstructive Sleep Apnea (OSA) monitoring indicators into three categories: physical, biochemical, and electrophysiological indicators, and lists several methods for each category. Abstract Obstructive sleep apnea (OSA) is a common chronic sleep‐disordered breathing disease characterized by recurrent upper airway ...
Yaowen Xu, Feifei Lin, Shujiao Chen, Zhen You, Shujing Zhu, Weiwei Zhao, Qiang Zhao   +6 more
wiley   +1 more source

Enhanced monopulse radar tracking using empirical mode decomposition [PDF]

, 2010
Monopulse radar processors are used to track targets that appear in the look direction beamwidth. The target tracking information (range, azimuth angle, and elevation angle) are affected when manmade high power interference (jamming) is introduced to the
Elgamel, Sherif A.E.H., Soraghan, J.J.
core  

Financial Market Prediction and Simulation Based on the FEPA Model

Journal of Mathematics, 2021
Since the birth of the financial market, the industry and academia want to find a method to accurately predict the future trend of the financial market.
Dehui Zhou
doaj   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source