Results 21 to 30 of about 406 (163)

The SSHVEP Paradigm-Based Brain Controlled Method for Grasping Robot Using MVMD Combined CNN Model

IEEE Transactions on Neural Systems and Rehabilitation Engineering
In recent years, the steady-state visual evoked potentials (SSVEP) based brain control method has been employed to help people with disabilities because of its advantages of high information transmission rate and low training time.
Shiqiang Yang, Jincao Zhou, Jing Luo
exaly   +5 more sources

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   +2 more sources

Fault feature extraction method for rolling bearing based on MVMD and complex Fourier transform [PDF]

Journal of Vibroengineering, 2022
The vibration signals caused by rolling bearing defects in different directions may be different, and the fault diagnosis based on single channel vibration signals may be made incorrectly, and the observation results may be understood wrong. To avoid it, a new rolling bearing fault feature extraction method based on multivariate variational mode ...
Chuanjin Huang, Haijun Song
openaire   +2 more sources

Airborne Radio-Echo Sounding Data Denoising Using Particle Swarm Optimization and Multivariate Variational Mode Decomposition

Remote Sensing, 2023
Radio-echo sounding (RES) is widely used for polar ice sheet detection due to its wide coverage and high efficiency. The multivariate variational mode decomposition (MVMD) algorithm for the processing of RES data is an improvement to the variational mode
Yuhan Chen, Sixin Liu, Kun Luo, Lijuan Wang, Xueyuan Tang   +4 more
doaj   +2 more sources

Ultra-Short-Term Wind Power Forecasting Using an NSGA-II-MVMD-BiLSTM Hybrid Model

Applied Sciences
Wind power forecasting is crucial for ensuring the stability and reliability of power systems as wind energy penetration increases. This study presents a hybrid model, NSGA-II-MVMD-BiLSTM, designed for ultra-short-term wind power prediction.
Jie Fu, Zongyou Xia, Siliu Yu, Gonghao Duan, Qiang Chen   +4 more
doaj   +2 more sources

A Field Verification Denoising Method for Partial Discharge Ultrasonic Sensors Based on IPSO-Optimated Multivariate Variational Mode Decomposition Combined with Improved Wavelet Transforms [PDF]

Sensors
Field verification of contact-type ultrasonic sensors enables rapid evaluation of their sensitivity performance, thereby ensuring the accuracy of partial discharge (PD) ultrasonic monitoring results.
Tienan Cao, Yufei Cui, Haotian Tan, Wei Lu, Fuzeng Zhang, Kai Liu, Xiaoguo Chen, Yifan Chen, Lujia Wang   +8 more
doaj   +2 more sources

Short-Term Load Forecasting for Residential Buildings Based on Multivariate Variational Mode Decomposition and Temporal Fusion Transformer

Energies
Short-term load forecasting plays a crucial role in managing the energy consumption of buildings in cities. Accurate forecasting enables residents to reduce energy waste and facilitates timely decision-making for power companies’ energy management.
Haoda Ye, Qiuyu Zhu, Xuefan Zhang
doaj   +2 more sources

Fault diagnosis method using MVMD signal reconstruction and MMDE-GNDO feature extraction and MPA-SVM [PDF]

Frontiers in Physics
To achieve a comprehensive and accurate diagnosis of faults in rolling bearings, a method for diagnosing rolling bearing faults has been proposed.
Min Mao, Chengjiang Zhou, Bingwei Xu, Dongjin Liao, Jingzong Yang, Shuangyao Liu, Yiqing Li, Tong Tang   +7 more
doaj   +2 more sources

Towards intelligent air quality forecasting using integrated machine learning framework with variational mode decomposition and catboost feature selection [PDF]

Scientific Reports
Predicting air pollution is crucial in improving air quality (AQ), which consequently provides benefits to the ecosystems and human health. AQ predictions often make use of Machine Learning (ML) approaches; nevertheless, these methods are not without ...
Iman Ahmadianfar, Zaher Mundher Yaseen, Haydar Abdulameer Marhoon, Bijay Halder, Mou Leong Tan, Huseyin Cagan Kilinc, Sani I. Abba, Salim Heddam, Leonardo Goliatt, Vahdettin Demir, Ahmed M. Al-Areeq   +10 more
doaj   +2 more sources

Forecasting of interval carbon price in China based on decomposition-reconstruction-ensemble framework [PDF]

Carbon Balance and Management
Accurate prediction of carbon prices is imperative for the effective management of carbon markets and the facilitation of a global transition to green energy.
Beibei Hu, Yunhe Cheng
doaj   +2 more sources