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A Hybrid Deep Learning Model for Link Dynamic Vehicle Count Forecasting with Bayesian Optimization

Journal of Advanced Transportation, Volume 2023, Issue 1, 2023., 2023
The link dynamic vehicle count is a spatial variable that measures the traffic state of road sections, which reflects the actual traffic demand. This paper presents a hybrid deep learning method that combines the gated recurrent unit (GRU) neural network model with automatic hyperparameter tuning based on Bayesian optimization (BO) and the improved ...
Chunguang He +4 more
wiley +1 more source

Joint MVMD-based optimal feature selection and FW-LS-TWSVM for motor imagery recognition. [PDF]

Sci Rep
Zhi J +7 more
europepmc +2 more sources

Evolving Trends in the Management of Acute Appendicitis During COVID‐19 Waves: The ACIE Appy II Study

World Journal of Surgery, Volume 46, Issue 9, Page 2021-2035, September 2022., 2022
Abstract Background In 2020, ACIE Appy study showed that COVID‐19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non‐operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this ...
Francesco Pata +405 more
wiley +1 more source

RF‐Gait: Gait‐Based Person Identification with COTS RFID

Wireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022
Recently, person identification has been a prerequisite in many applications of the Internet of Things. As a new biometric identification technology, gait recognition has a wide application prospect with the advantages of long‐distance recognition and difficulty to forge.
Shang Jiang +7 more
wiley +1 more source

Fault diagnosis of sensor pulse signals based on improved energy fluctuation index and VMD

Frontiers in Physics, 2023
Variational mode decomposition (VMD) has been widely applied in sensors. However, the mode number and balance parameter seriously limit VMD application.
Yuhu Liu +4 more
doaj +1 more source

Fault Diagnosis of the Gyratory Crusher Based on Fast Entropy Multilevel Variational Mode Decomposition

Shock and Vibration, Volume 2021, Issue 1, 2021., 2021
Gyratory crusher is a kind of commonly used mining machinery. Because of its heavy workload and complex working environment, it is prone to failure and low reliability. In order to solve this problem, this paper proposes a fault diagnosis method of the gyratory crusher based on fast entropy multistage VMD, which is used to quickly and accurately find ...
Fengbiao Wu +5 more
wiley +1 more source

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 +3 more
doaj +1 more source

Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach

, 2023
Reference evapotranspiration can cause huge discrepancies in soil moisture and runoff which is responsible for uncertainties in drought warning systems.
M Karbasi (13305330) +6 more
core +2 more sources

A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture

, 2023
The objective of this study is to develop a novel multi-level pre-processing framework and apply it for multi-step (one and seven days ahead) daily forecasting of Surface soil moisture (SSM) based on the NASA’s Soil Moisture Active Passive (SMAP ...
Jamei, Mozhdeh +6 more
core +1 more source

Correction: Evolving Trends in the Management of Acute Appendicitis During COVID‐19 Waves: The ACIE Appy II Study

, 2023
World Journal of Surgery, Volume 47, Issue 1, Page 285-285, January 2023.
Francesco Pata +405 more
wiley +1 more source

multivariate variational mode decomposition
multivariate variational mode decomposition mvmd
fault diagnosis

vmd
feature extraction
variational mode decomposition

deep learning