ForecastingAccurate 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 +3 more
doaj +1 more source
Data-driven Signal Decomposition Approaches: A Comparative Analysis
, 2022 Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent amplitude- and frequency-modulated components. This represents an important preprocessing step in many practical signal processing pipelines, providing ...
Eriksen, Thomas, Rehman, Naveed ur
core
Subsynchronous Oscillation Source Location in Power System with High Penetration of Wind Power Using Multivariate Variational Mode Decomposition [PDF]
Accurately and promptly extracting subsynchronous oscillation (SSO) components from measurements and locating SSO sources are crucial for SSO suppression.
Huang, Tao +6 more
core +1 more source
Time-Domain Electromagnetic Noise Suppression Using Multivariate Variational Mode Decomposition
Remote SensingNoise suppression is essential in time-domain electromagnetic (TDEM) data processing and interpretation. TDEM data are typically in broadband signal, which makes it difficult to separate the signal in the whole frequency band.
Kang Xing +3 more
doaj +1 more source
Frontiers in Artificial IntelligenceShort-term load forecasting plays a vital role in today's modern life to ensure the balance between energy demand and supply. Dynamic variations in weather and electricity consumption patterns can significantly influence load patterns, resulting in ...
Radhika Chandrasekaran +1 more
doaj +1 more source
A LOGIT ANALYSIS OF PARTICIPATION IN TENNESSEE'S FOREST STEWARDSHIP PROGRAM [PDF]
This study determines the likely effect of cost-share incentives on participation in the Tennessee Forest Stewardship Program and identifies other factors that may contribute to participation.
Bell, Caroline D. +3 more
core +1 more source
Short-term forecasting of building heating load based on MVMD-SSA-LSTM
Clean Energy Science and TechnologyA short-term heating load forecast for buildings is a critical step in the subsequent control of energy systems, directly impacting system energy consumption. However, given that heating load and its influencing factors constitute volatile time series data, noise interference within the data significantly limits prediction accuracy and stability.
Bo Zhou +5 more
openaire +1 more source
Enhancing Alzheimer’s detection from EEG using MVMD and feature optimization algorithm
Journal of King Saud University – ScienceAlzheimer’s disease (AD) is a neurodegenerative disorder causing progressive cognitive decline, often associated with slower electroencephalogram activity (EEG) and reduced neural synchronization. Although EEG is important for diagnosing AD, distinguishing signals from individuals with mild cognitive impairment (MCI) or AD is challenging.
Ibrahim Al-Shourbaji, Abdalla Alameen
openaire +1 more source
Effectiveness of aquatic phytoremediation of nutrients via watercress (Nasturtium officinale), basil (Ocimum basilicum), dill (Anethum graveolens) and lettuce (Lactuca sativa) from effluent of a flow-through aquaculture operation [PDF]
, 2006 Effluent from the aquaculture industry is a source of nutrient loading upon water bodies nationwide. Aquaponics, the simultaneous cultivation of fish and plants, has the potential to effectively reduce nutrient concentrations through phytoremediation ...
Dyer, Derek J.
core +1 more source
Mine cable partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold [PDF]
The insulation state of the mine cable plays an important role in the stable operation of the mine power supply system. Partial discharge on-line monitoring is an important means of cable insulation state monitoring.
Jiyuan CAO +6 more
core +1 more source