Results 31 to 40 of about 226 (142)

Gearbox fault diagnosis method based on MVMD-MOMEDA [PDF]

open access: yesJournal of Hebei University of Science and Technology, 2023
Aiming at the problem that the early weak fault diagnosis of gearbox vibration signal is difficult due to the influence of complex transmission path and strong background noise, a gearbox fault diagnosis method based on multivariate variational mode ...
Suxiao CUI   +4 more
doaj   +1 more source

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

open access: yesJournal 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

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

open access: yesWireless 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

GPR Energy Attribute Slices Based on Multivariate Variational Mode Decomposition and Teager–Kaiser Energy Operator

open access: yesRemote Sensing, 2022
The GPR signals appear nonlinear and nonstationary during propagation. To evaluate the nonstationarity, the empirical mode decomposition (EMD) and its modifications have been proposed to localize the variations of energy and frequency components over ...
Xuebing Zhang   +5 more
doaj   +1 more source

Evaporation and soil moisture prediction with artificial intelligence and deep learning methods [PDF]

open access: yes, 2023
Understanding future changes and predicting hydrological variables well in advance is practically useful in water resources and drought management measures.
Jayasinghe Mudiyanselage, W.J.M. Lakmini Prarthana
core   +1 more source

A non-parametric algorithm for time-dependent modal analysis of civil structures and infrastructures [PDF]

open access: yes, 2023
Vibration-based monitoring strategies have been demonstrated to be effective tools in providing - in nearly real-time - reliable information regarding the integrity of structures and infrastructure systems.
Barontini, Alberto   +3 more
core   +1 more source

Editorial: Advanced methods in signal processing, image processing and pattern recognition in geosciences [PDF]

open access: yes, 2023
Indexación: Scopus.Lately, applications of signal processing, image processing, and pattern recognition have been widely introduced in geosciences, such as in the context of natural resources exploration, either petroleum or mineral, and engineering ...
Mohammed Farfour   +2 more
core   +1 more source

Adaptive noise suppression for low-S/N microseismic data based on ambient-noise-assisted multivariate empirical mode decomposition [PDF]

open access: yes, 2023
Microseismic monitoring data may be seriously contaminated by complex and nonstationary interference noises produced by mechanical vibration, which significantly impact the data quality and subsequent data-processing procedure.
Chuan He   +5 more
core   +1 more source

A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy

open access: yesShock and Vibration, Volume 2020, Issue 1, 2020., 2020
Vibration signal, as an important means for diesel engine condition detection and fault diagnosis, has attracted attention for many years. In traditional vibration signal analysis, most processing methods are for single‐channel data. However, single‐channel vibration signal cannot reflect the operating information of the diesel engine comprehensively ...
Cheng Gu   +4 more
wiley   +1 more source

Performance Analysis of Deep-Learning and Explainable AI Techniques for Detecting and Predicting Epileptic Seizures [PDF]

open access: yes, 2023
Epilepsy is one of the most common neurological diseases globally. Notably, people in low to middle-income nations could not get proper epilepsy treatment due to the cost and availability of medical infrastructure. The risk of sudden unpredicted death in
Patil, Ashwini, Patil, Megharani
core   +2 more sources

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