Event prediction in the big data era: A systematic survey
L Zhao - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …
either our society or the nature, such as earthquakes, civil unrest, system failures …
Application of artificial intelligence in predicting earthquakes: state-of-the-art and future challenges
Predicting the time, location and magnitude of an earthquake is a challenging job as an
earthquake does not show specific patterns resulting in inaccurate predictions. Techniques …
earthquake does not show specific patterns resulting in inaccurate predictions. Techniques …
[HTML][HTML] Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations
S Gupta, S Modgil, A Kumar, U Sivarajah… - International Journal of …, 2022 - Elsevier
Natural disasters are often unpredictable and therefore there is a need for quick and
effective response to save lives and infrastructure. Hence, this study is aimed at achieving …
effective response to save lives and infrastructure. Hence, this study is aimed at achieving …
[HTML][HTML] Early detection of earthquake magnitude based on stacked ensemble model
A new machine learning model, named, EEWPEnsembleStack has been developed for
predicting the magnitude of the earthquake from a few seconds of recorded ground motion …
predicting the magnitude of the earthquake from a few seconds of recorded ground motion …
A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data
A suitable combination of linear and nonlinear models provides a more accurate prediction
model than an individual linear or nonlinear model for forecasting time series data …
model than an individual linear or nonlinear model for forecasting time series data …
A hybrid ETS–ANN model for time series forecasting
S Panigrahi, HS Behera - Engineering applications of artificial intelligence, 2017 - Elsevier
Over the past few decades, a large literature has evolved to forecast time series using
various linear, nonlinear and hybrid linear–nonlinear models. Recently, hybrid models by …
various linear, nonlinear and hybrid linear–nonlinear models. Recently, hybrid models by …
Earthquake magnitude prediction in Hindukush region using machine learning techniques
Earthquake magnitude prediction for Hindukush region has been carried out in this research
using the temporal sequence of historic seismic activities in combination with the machine …
using the temporal sequence of historic seismic activities in combination with the machine …
Earthquake prediction model using support vector regressor and hybrid neural networks
Earthquake prediction has been a challenging research area, where a future occurrence of
the devastating catastrophe is predicted. In this work, sixty seismic features are computed …
the devastating catastrophe is predicted. In this work, sixty seismic features are computed …
Neural network applications in earthquake prediction (1994–2019): Meta‐analytic and statistical insights on their limitations
A Mignan, M Broccardo - Seismological Research …, 2020 - pubs.geoscienceworld.org
In the last few years, deep learning has solved seemingly intractable problems, boosting the
hope to find approximate solutions to problems that now are considered unsolvable …
hope to find approximate solutions to problems that now are considered unsolvable …
[HTML][HTML] Spatiotemporally explicit earthquake prediction using deep neural network
M Yousefzadeh, SA Hosseini, M Farnaghi - Soil Dynamics and Earthquake …, 2021 - Elsevier
Due to the complexity of predicting future earthquakes, machine learning algorithms have
been used by several researchers to increase the Accuracy of the forecast. However, the …
been used by several researchers to increase the Accuracy of the forecast. However, the …