Results 31 to 40 of about 3,491,274 (129)

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

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
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Enhanced Deep Representation Learning Extreme Learning Machines for EV Charging Load Forecasting by Improved Artemisinin Optimization and Multivariate Variational Mode Decomposition

Energies
The Electric Vehicle (EV) industry is developing rapidly, and EVs are becoming an increasingly important choice for the future of transportation. Therefore, accurately forecasting the electricity demand for EVs is crucial.
Anjie Zhong, Honghai Li, Zhongyi Tang, Zhirong Zhang   +3 more
doaj   +2 more sources

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   +2 more sources

Multiscale Functional Connectivity analysis of episodic memory reconstruction [PDF]

Frontiers in Cognition
Our ability to share memories constitutes a social foundation of our world. When exposed to another person's memory, individuals can mentally reconstruct the events described, even if they were not present during the related events.
Manuel Morante, Kristian Frølich, Muhammad Shahzaib, Sadia Shakil, Naveed ur Rehman   +4 more
doaj   +2 more sources

A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting [PDF]

Scientific Reports
The precise monitoring and timely alerting of river water levels represent critical measures aimed at safeguarding the well-being and assets of residents in river basins.
Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen   +5 more
doaj   +2 more sources

A robust multi-model framework for groundwater level prediction: The BFSA-MVMD-GRU-RVM model

Results in Engineering
Groundwater level prediction is critical for environmental protection and agricultural planning. Accurate predictions help manage risks associated with excessive groundwater extraction and land subsidence.
Akram Seifi, Sharareh Pourebrahim, Mohammad Ehteram, Hanieh Shabanian   +3 more
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Seismic Random Noise Denoising Using Mini-Batch Multivariate Variational Mode Decomposition. [PDF]

Comput Intell Neurosci, 2022
Seismic noise attenuation plays an important role in seismic interpretation. The empirical mode decomposition, synchrosqueezing wavelet transform, variational mode decomposition, etc., are often applied trace by trace. Multivariate empirical mode decomposition, multivariate synchrosqueezing wavelet transform, and multivariate variational mode ...
Wu G, Liu G, Wang J, Fan P.
europepmc   +2 more sources

Multivariate Nonlinear Sparse Mode Decomposition and Its Application in Gear Fault Diagnosis

IEEE Access, 2021
Multi-channel signal has more abundant and accurate state characteristic information than single channel signal. How to separate fault characteristic information from the multi-channel signal is the key of fault diagnosis.
Haiyang Pan, Wanwan Jiang, Qingyun Liu, Jinde Zheng   +3 more
doaj   +1 more source

Detecting and Diagnosing Process Nonlinearity- Induced Unit-Wide Oscillations Based on an Optimized Multivariate Variational Mode Decomposition Method

IEEE Access, 2022
In process control system, nonlinearity-induced unit-wide oscillations are a common fault, which degrades the control performance and threaten the stability.
Zhuliang Lin, Min Sun, Xialai Wu
doaj   +1 more source