[HTML][HTML] The role of artificial intelligence and IoT in prediction of earthquakes

J Pwavodi, AU Ibrahim, PC Pwavodi… - Artificial Intelligence in …, 2024 - Elsevier
Earthquakes are classified as one of the most devastating natural disasters that can have
catastrophic effects on the environment, lives, and properties. Most recent devastating …

[HTML][HTML] Artificial intelligence in environmental monitoring: Advancements, challenges, and future directions

DB Olawade, OZ Wada, AO Ige, BI Egbewole… - Hygiene and …, 2024 - Elsevier
Abstract The application of Artificial Intelligence (AI) in environmental monitoring offers
accurate disaster forecasts, pollution source detection, and comprehensive air and water …

Artificial neural network model with different backpropagation algorithms and meteorological data for solar radiation prediction

SY Heng, WM Ridwan, P Kumar, AN Ahmed, CM Fai… - Scientific reports, 2022 - nature.com
Solar energy serves as a great alternative to fossil fuels as they are clean and renewable
energy. Accurate solar radiation (SR) prediction can substantially lower down the impact …

Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms

MA Murti, R Junior, AN Ahmed, A Elshafie - Scientific reports, 2022 - nature.com
Earthquake is one of the natural disasters that have a big impact on society. Currently, there
are many studies on earthquake detection. However, the vibrations that were detected by …

Machine learning for earthquake prediction: a review (2017–2021)

NSM Ridzwan, SHM Yusoff - Earth Science Informatics, 2023 - Springer
For decades, earthquake prediction has been the focus of research using various methods
and techniques. It is difficult to predict the size and location of the next earthquake after one …

Predicting the likelihood of an earthquake by leveraging volumetric statistical data through machine learning techniques

M Nurtas, Z Zhantaev, A Altaibek, S Nurakynov… - Engineered …, 2023 - espublisher.com
This research paper presents an analysis of a dataset covering significant earthquakes over
the past century, sourced from a publicly accessible seismic database. The dataset includes …

Internal Friction Angle of Cohesionless Binary Mixture Sand–Granular Rubber Using Experimental Study and Machine Learning

F Daghistani, A Baghbani, H Abuel Naga… - Geosciences, 2023 - mdpi.com
This study aimed to examine the shear strength characteristics of sand–granular rubber
mixtures in direct shear tests. Two different sizes of rubber and one of sand were used in the …

Kalman Filter, ANN-MLP, LSTM and ACO methods showing anomalous gps-tec variations concerning Turkey's powerful earthquake (6 February 2023)

M Akhoondzadeh - Remote Sensing, 2023 - mdpi.com
On 6 February 2023, at 1: 17: 34 UTC, a powerful Mw= 7.8 earthquake shook parts of Turkey
and Syria. Investigating the behavior of different earthquake precursors around the time and …

A systematic review of Earthquake Early Warning (EEW) systems based on Artificial Intelligence

P Kolivand, P Saberian, M Tanhapour, F Karimi… - Earth Science …, 2024 - Springer
Abstract Early Earthquake Warning (EEW) systems alarm about ongoing earthquakes to
reduce their devastating human and financial damages. In complicated tasks like …

[PDF][PDF] Abuel Naga, H.; Faradonbeh, RS Internal Friction Angle of Cohesionless Binary Mixture Sand–Granular Rubber Using Experimental Study and Machine …

F Daghistani, A Baghbani - Geosciences, 2023 - academia.edu
This study aimed to examine the shear strength characteristics of sand–granular rubber
mixtures in direct shear tests. Two different sizes of rubber and one of sand were used in the …