Results 41 to 50 of about 3,491,274 (129)

Gearbox fault diagnosis method based on MVMD-MOMEDA [PDF]

Journal of Hebei University of Science and Technology, 2023
Aiming at the problem that the early weak fault diagnosis of gearbox vibration signal is difficult due to the influence of complex transmission path and strong background noise, a gearbox fault diagnosis method based on multivariate variational mode ...
Suxiao CUI, Yanping CUI, Zhe WU, Zhiyuan LYU, Linlin ZHANG   +4 more
doaj   +1 more source

Short-Term Photovoltaic Power Generation Prediction Model Based on Improved Data Decomposition and Time Convolution Network

Energies, 2023
In response to the volatility of photovoltaic power generation, this paper proposes a short-term photovoltaic power generation prediction model (HWOA-MVMD-TPA-TCN) based on a Hybrid Whale Optimization Algorithm (HWOA), multivariate variational mode ...
Ranran Cao, He Tian, Dahua Li, Mingwen Feng, Huaicong Fan   +4 more
doaj   +1 more source

A Hybrid Deep Learning Model for Link Dynamic Vehicle Count Forecasting with Bayesian Optimization

Journal of Advanced Transportation, Volume 2023, Issue 1, 2023., 2023
The link dynamic vehicle count is a spatial variable that measures the traffic state of road sections, which reflects the actual traffic demand. This paper presents a hybrid deep learning method that combines the gated recurrent unit (GRU) neural network model with automatic hyperparameter tuning based on Bayesian optimization (BO) and the improved ...
Chunguang He, Dianhai Wang, Yi Yu, Zhengyi Cai, Young-Jae Lee   +4 more
wiley   +1 more source

RF‐Gait: Gait‐Based Person Identification with COTS RFID

Wireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022
Recently, person identification has been a prerequisite in many applications of the Internet of Things. As a new biometric identification technology, gait recognition has a wide application prospect with the advantages of long‐distance recognition and difficulty to forge.
Shang Jiang, Jianguo Jiang, Siye Wang, Yanfang Zhang, Yue Feng, Ziwen Cao, Yi Liu, Yinghui Ye   +7 more
wiley   +1 more source

Noise-Assisted Multivariate Variational Mode Decomposition

, 2021
The variational mode decomposition (VMD) is a widely applied optimization-based method, which analyzes non-stationary signals concurrently. Correspondingly, its recently proposed multivariate extension, i.e., MVMD, has shown great potentials in analyzing
Hadjileontiadis, Leontios, Charilaos A. Zisou, Apostolidis, Georgios, Georgios K. Apostolidis, Zisou, Charilaos, Leontios J. Hadjileontiadis   +5 more
core   +1 more source

A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy

Shock and Vibration, Volume 2020, Issue 1, 2020., 2020
Vibration signal, as an important means for diesel engine condition detection and fault diagnosis, has attracted attention for many years. In traditional vibration signal analysis, most processing methods are for single‐channel data. However, single‐channel vibration signal cannot reflect the operating information of the diesel engine comprehensively ...
Cheng Gu, Xinyong Qiao, Ying Jin, Yanbin Liu, Rafał Burdzik   +4 more
wiley   +1 more source

Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation

, 2023
Significant wave height is an average of the largest ocean waves, which are important for renewable and sustainable energy resource generation. A large significant wave height can cause beach erosion, and marine navigation problems in a storm.
Mehdi Jamei, Yong Xiang, Shahab Abdulla, Farooque, Aitazaz A., Abdulla, Shahab, Zheng, Zihao, Zihao Zheng, Zaher Mundher Yaseen, Yaseen, Zaher Mundher, Aitazaz A. Farooque, Ali, Mumtaz, Mumtaz Ali, Jamei, Mehdi, Xiang, Yong   +13 more
core   +1 more source

Advanced ADHD Detection Using Multivariate Variational Mode Decomposition and Deep Learning: A Novel EEG-Based Framework [PDF]

InfoScience Trends
This study proposes a novel framework for detecting Attention Deficit Hyperactivity Disorder (ADHD) using electroencephalography (EEG) signals, integrating multivariate variational mode decomposition (MVMD) with machine learning techniques.
Parastou Shahmohamadi, Shiva Amini, Shiva Khanbabaee, Negin Tavakoli, Sedigheh Molaei, Niloofar Teimoori   +5 more
doaj   +1 more source

Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach

, 2022
Accurate forecasting of the wave energy is crucial and has significant potential because every wave meter possesses an energy amount ranging from 30 to 40 kW along the shore.
Yaseen, Zaher Mundher, Ali, Mumtaz, Karbasi, Masoud, Jamei, Mehdi, Xiang, Yong, Ahmadianfar, Iman   +5 more
core   +1 more source

ROTOR FAULT FEATURE EXTRACTION METHOD USING MVMD AND IEDPE (MT)

, 2023
To accurately characterize the different operating states of the rotor system, a modified variational mode decomposition（MVMD） combined with instantaneous energy distribution permutation entropy（IEDPE） is proposed to quantify and extract rotor fault ...
GUO XiaoBo, WU YaoChun, WU Jie, JIA XiaoFeng, DU ShaoHua, ZHAO Yan, JU Hai   +6 more
core   +1 more source