Results 61 to 70 of about 226 (142)

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

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   +1 more source

Series-Core Fusion Based Multivariate Variational Mode Decomposition for Short-Term Wind Power Prediction Using Multiple Meteorological Data

Forecasting
Accurate wind power forecasting is critical for enhancing the operational efficiency and stability of electrical power grids. Conventional single-variable signal decomposition forecasting methods ignore the coupling relationship between wind power and ...
Wentian Lu, Zhenming Lu, Wenjie Liu, Yifeng Cao   +3 more
doaj   +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
Charilaos A. Zisou, Georgios K. Apostolidis, Leontios J. Hadjileontiadis   +2 more
core   +2 more sources

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.
Abdulla, Shahab, Ali, Mumtaz, Farooque, Aitazaz A., Jamei, Mehdi, Xiang, Yong, Yaseen, Zaher Mundher, Zheng, Zihao   +6 more
core   +1 more source

Short-Term Photovoltaic Power Generation Based on MVMD Feature Extraction and Informer Model

Applied Sciences
Photovoltaic (PV) power fluctuates with weather changes, and traditional forecasting methods typically decompose the power itself to study its characteristics, ignoring the impact of multidimensional weather conditions on the power decomposition ...
Ruilin Xu, Jianyong Zheng, Fei Mei, Xie Yang, Yue Wu, Heng Zhang   +5 more
doaj   +1 more source

Solar loading infrared thermography method for the non-invasive inspection of movable arts: The contribution of Multivariate Fast Iterative Filtering and Multidimensional Fast Iterative Filtering for 2D data techniques [PDF]

This work is focalized on the application of two recent techniques, i.e. Multivariate Fast Iterative Filtering (MvFIF) and Multidimensional Fast Iterative Filtering for 2D data (FIF2), that have demonstrated their ability in the pre-processing phase of ...
Cicone, Antonio, Ding, Yinuo, Pellegrino, Enza, Russo, Gilda, Sfarra, Stefano, Tshiangomba, Reagan Kasonsa, Zhang, Hai   +6 more
core   +1 more source

1D-CapsNet-LSTM: A Deep Learning-Based Model for Multi-Step Stock Index Forecasting

, 2023
Multi-step stock index forecasting is vital in finance for informed decision-making. Current forecasting methods on this task frequently produce unsatisfactory results due to the inherent data randomness and instability, thereby underscoring the demand ...
Ibrahim, Roslina, Sjarif, Nilam Nur Amir, Zhang, Cheng   +2 more
core  

Dynamic graph structure and spatio-temporal representations in wind power forecasting [PDF]

Wind Power Forecasting (WPF) has gained considerable focus as a crucial aspect of the successful integration and operation of wind power. However, due to the stochastic and unstable nature of wind, it poses a real challenge to effectively analyze the ...
Dong Wenqi, Fu Jianglong, Wang Jing, Zang Peng   +3 more
core   +1 more source

Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations [PDF]

Emotion recognition is the ability to precisely infer human emotions from numerous sources and modalities using questionnaires, physical signals, and physiological signals.
Acharya, U. Rajendra, Blanes-Vidal, Victoria, Khare, Smith K., Nadimi, Esmaeil S.   +3 more
core   +2 more sources

Prediction of Sea Level Using Double Data Decomposition and Hybrid Deep Learning Model for Northern Territory, Australia

Mathematics
Sea level rise (SLR) attributed to the melting of ice caps and thermal expansion of seawater is of great global significance to vast populations of people residing along the world’s coastlines.
Nawin Raj, Jaishukh Murali, Lila Singh-Peterson, Nathan Downs   +3 more
doaj   +1 more source