Employing machine learning and iot for earthquake early warning system in smart cities
An earthquake early warning system (EEWS) should be included in smart cities to preserve
human lives by providing a reliable and efficient disaster management system. This system …
human lives by providing a reliable and efficient disaster management system. This system …
Deep learning, machine learning and internet of things in geophysical engineering applications: An overview
Abstract The earthquakes in Eastern Mediterranean are mostly tectonic. The earthquakes
that are 60 km deep in the ground are called Shallow earthquakes. The earthquakes in the …
that are 60 km deep in the ground are called Shallow earthquakes. The earthquakes in the …
Seismic intensity estimation for earthquake early warning using optimized machine learning model
MS Abdalzaher, MS Soliman… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The need for an earthquake early-warning system (EEWS) is unavoidable to save lives. In
terms of managing earthquake disasters and achieving effective risk mitigation, the quick …
terms of managing earthquake disasters and achieving effective risk mitigation, the quick …
A deep learning model for earthquake parameters observation in IoT system-based earthquake early warning
MS Abdalzaher, MS Soliman… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Earthquake early-warning system (EEWS) is inevitable for saving human lives. The fast
determination of the Earthquake's (EQ's) magnitude and its location is significant in disaster …
determination of the Earthquake's (EQ's) magnitude and its location is significant in disaster …
Deep learning reservoir porosity prediction based on multilayer long short-term memory network
The cost of obtaining a complete porosity value using traditional coring methods is relatively
high, and as the drilling depth increases, the difficulty of obtaining the porosity value also …
high, and as the drilling depth increases, the difficulty of obtaining the porosity value also …
Deep learning seismic random noise attenuation via improved residual convolutional neural network
Because a high signal-to-noise ratio (SNR) is beneficial to the subsequent processing
procedures, the noise attenuation is important. We propose an adaptive random noise …
procedures, the noise attenuation is important. We propose an adaptive random noise …
Employing remote sensing, data communication networks, ai, and optimization methodologies in seismology
MS Abdalzaher, HA Elsayed… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Seismology is among the intrinsic sciences that strictly affect human lives. Many research
efforts are presented in the literature aiming at achieving risk mitigation and disaster …
efforts are presented in the literature aiming at achieving risk mitigation and disaster …
ADDCNN: An attention-based deep dilated convolutional neural network for seismic facies analysis with interpretable spatial–spectral maps
F Li, H Zhou, Z Wang, X Wu - IEEE Transactions on Geoscience …, 2020 - ieeexplore.ieee.org
With the dramatic growth and complexity of seismic data, manual seismic facies analysis has
become a significant challenge. Machine learning and deep learning (DL) models have …
become a significant challenge. Machine learning and deep learning (DL) models have …
Facies identification based on multikernel relevance vector machine
Facies identification is a powerful means to predict reservoirs. We achieve facies
identification using a relevance vector machine (RVM) and develop a facies discriminant …
identification using a relevance vector machine (RVM) and develop a facies discriminant …
Deep learning approach for earthquake parameters classification in earthquake early warning system
Magnitude determination of earthquakes is a mandatory step before an earthquake early
warning (EEW) system sends an alarm. Beneficiary users of EEW systems dependon how …
warning (EEW) system sends an alarm. Beneficiary users of EEW systems dependon how …