Missing data problem in the monitoring system: A review

J Du, M Hu, W Zhang - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Missing data is a common phenomenon in sensor networks, especially in the large-scale
monitoring system. It can be affected by various kinds of reasons. Moreover, incomplete data …

A methodology for data gap filling in wave records using Artificial Neural Networks

F Vieira, G Cavalcante, E Campos… - Applied Ocean …, 2020 - Elsevier
Wave measuring equipment are subject to malfunction that can be caused by various
reasons such as maintenance, navigation accidents, errors in communications and …

Novel time-efficient approach to calibrate VARANS-VOF models for simulation of wave interaction with porous structures using Artificial Neural Networks

F Vieira, F Taveira-Pinto, P Rosa-Santos - Ocean Engineering, 2021 - Elsevier
Numerical models are valuable tools to provide information on wave-structure interaction
processes that are difficult to measure in a physical model. The current level of accuracy of …

A deep learning method for data recovery in sensor networks using effective spatio-temporal correlation data

J Du, H Chen, W Zhang - Sensor Review, 2019 - emerald.com
Purpose In large-scale monitoring systems, sensors in different locations are deployed to
collect massive useful time-series data, which can help in real-time data analytics and its …

Filling gaps in significant wave height time series records using bidirectional gated recurrent unit and cressman analysis

J Wang, K Wen, F Deng - Dynamics of Atmospheres and Oceans, 2023 - Elsevier
Continuous records of wave data are of great significance for marine researches and
analyses. However, the measurement of wave by buoys is often interrupted for various …

Evolutionary modeling of inclined dense jets discharged from multiport diffusers

X Yan, A Mohammadian - Journal of Coastal Research, 2020 - meridian.allenpress.com
ABSTRACT Yan, X. and Mohammadian, A., 2020. Evolutionary modeling of inclined dense
jets discharged from multiport diffusers. Journal of Coastal Research, 36 (2), 362–371 …

Neural network modeling of monthly salinity variations in oyster reef in Apalachicola Bay in response to freshwater inflow and winds

D Le, W Huang, E Johnson - Neural Computing and Applications, 2019 - Springer
Estuarine organisms have varying tolerances and respond differently to salinity. Bottom-
dwelling species such as oysters tolerate some change in salinity, but salinity outside an …

Sensor Data Recovery of Faulty Rocket Engine Based on Multistage Graph Convolutional Network

Q Li, X Li, W Zhang, W Yao - Journal of Spacecraft and Rockets, 2023 - arc.aiaa.org
Engine, the indispensable core of a rocket, has a significant impact on space exploration,
especially the high-thrust liquid-propellant rocket engine. Most new-generation manned …

Automatic tracking and intelligent observation of tidal bore propagation velocity based on UAV and computer vision

X Zhang, G Zhan, T Ding, H Jiang… - Measurement and …, 2024 - journals.sagepub.com
The rapidly developed Unmanned Aerial Vehicles (UAV) and artificial intelligence
technology has prompted the real-time and accurate observation measurements of tidal …

Simulation of Remote-Sensed Chlorophyll Concentration with a Coupling Model Based on Numerical Method and CA-SVM in Bohai Bay, China

X **ang, W Lu, X Cui, Z Li, J Tao - Journal of Coastal …, 2018 - meridian.allenpress.com
ABSTRACT **ang, X.; Lu, W.; Cui, X.; Li, Z., and Tao, J., 2018. Simulation of remote-sensed
chlorophyll concentration with a coupling model based on numerical method and CA-SVM …