Results 51 to 60 of about 406 (163)

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.
M Karbasi (13305330), ZM Yaseen (13896354), I Ahmadianfar (13896351), Yong Xiang (13101027), Mumtaz Ali (13057623), M Jamei (13305324)   +5 more
core   +2 more sources

Research on the Fault Diagnosis Method for Rolling Bearings Based on Improved VMD and Automatic IMF Acquisition

Shock and Vibration, Volume 2020, Issue 1, 2020., 2020
This paper proposes a novel method to improve the variational mode decomposition (VMD) method and to automatically acquire the sensitive intrinsic mode function (IMF). First, since fault signals are impulsive and periodic, a weighted autocorrelative function maximum (AFM) indicator is constructed based on the Gini index and autocorrelation function to ...
Ying Zhang, Anchen Wang, Riccardo Rubini
wiley   +1 more source

Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection

, 2022
Accurate ahead forecasting of reference evapotranspiration (ETo) is crucial for effective irrigation scheduling and management of water resources on a regional scale.
Mehdi Jamei, Yaseen, Zaher Mundher, Masoud Karbasi, Prasad, Ramendra, Malik, Anurag, Ali, Mumtaz, Anurag Malik, Ramendra Prasad, Mumtaz Ali, Karbasi, Masoud, Jamei, Mehdi, Zaher Mundher Yaseen   +11 more
core   +2 more sources

A Session‐Based Song Recommendation Approach Involving User Characterization along the Play Power‐Law Distribution

Complexity, Volume 2020, Issue 1, 2020., 2020
In recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated.
Diego Sánchez-Moreno, Vivian F. López Batista, M. Dolores Muñoz Vicente, Ana B. Gil González, María N. Moreno-García, Átila Bueno   +5 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

Sub-Bottom Sediment Classification Using Reliable Instantaneous Frequency Calculation and Relaxation Time Estimation

Remote Sensing, 2021
The shift in IF (instantaneous frequency) series and the corresponding relaxation time have the potential to characterize sediment properties. However, these attributes derived from SBP (sub-bottom profiler) data are seldom used for offshore site ...
Shaobo Li, Jianhu Zhao, Hongmei Zhang, Siheng Qu   +3 more
doaj   +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

Multichannel Signal Denoising Using Multivariate Variational Mode Decomposition With Subspace Projection

IEEE Access, 2020
This paper describes a novel multichannel signal denoising approach based on multivariate variational mode decomposition (MVMD). MVMD is the extended version of the variational mode decomposition (VMD) algorithm for multichannel data sets.
Peipei Cao, Huali Wang, Kaijie Zhou
doaj   +1 more source

An Adaptive Forecasting Framework for EV Charging Demand Using Variational Mode Decomposition and Louvain Community Detection

IET Smart Grid, Volume 9, Issue 1, January/December 2026.
A novel framework for short‐term EV charging load forecasting has been developed and evaluated in this study. The integration of variational mode decomposition (VMD) with Louvain community detection provides a robust mechanism for capturing the multi‐scale characteristics inherent in EV charging demand.
Qiong Wang, Linru Jiang, Qinghe Sun, Chenjie Yan, Jiawei Li, Xi Zhang   +5 more
wiley   +1 more source