Application of artificial intelligence in predicting earthquakes: state-of-the-art and future challenges

MH Al Banna, KA Taher, MS Kaiser, M Mahmud… - IEEE …, 2020 - ieeexplore.ieee.org
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 risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

P Yariyan, H Zabihi, ID Wolf, M Karami… - International Journal of …, 2020 - Elsevier
Earthquakes are natural phenomena, which induce natural hazard that seriously threatens
urban areas, despite significant advances in retrofitting urban buildings and enhancing the …

[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 …

A location-dependent earthquake prediction using recurrent neural network algorithms

A Berhich, FZ Belouadha, MI Kabbaj - Soil Dynamics and Earthquake …, 2022 - Elsevier
In this paper, we propose a location-dependent earthquake prediction based on recurrent
neural network algorithms. The location-dependent prediction consists of clustering the …

On the Correction of Spatial and Statistical Uncertainties in Systematic Measurements of 222Rn for Earthquake Prediction

F Külahcı, Z Şen - Surveys in Geophysics, 2014 - Springer
In earthquake prediction studies, the regional behaviour of accurate 222 Rn measurements
at a set of sites plays a significant role. Here, measurements are obtained using active and …

Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula

F Martínez-Álvarez, J Reyes, A Morales-Esteban… - Knowledge-Based …, 2013 - Elsevier
This work explores the use of different seismicity indicators as inputs for artificial neural
networks. The combination of multiple indicators that have already been successfully used …

[HTML][HTML] Earthquakes magnitude predication using artificial neural network in northern Red Sea area

ASN Alarifi, NSN Alarifi, S Al-Humidan - Journal of King Saud University …, 2012 - Elsevier
Since early ages, people tried to predicate earthquakes using simple observations such as
strange or atypical animal behavior. In this paper, we study data collected from past …

Identification of earthquake precursors in soil radon-222 data of Kutch, Gujarat, India using empirical mode decomposition based Hilbert Huang Transform

SK Sahoo, M Katlamudi, C Barman… - Journal of Environmental …, 2020 - Elsevier
Abstract Soil radon (Rn-222) has been continuously monitored at Badargadh station (23.47°
N, 70.62° E) in Kutch region of Gujarat to study the pre-seismic anomalies prior to …

[HTML][HTML] A BP artificial neural network model for earthquake magnitude prediction in Himalayas, India

S Narayanakumar, K Raja - Circuits and Systems, 2016 - scirp.org
The aim of this study is to evaluate the performance of BP neural network techniques in
predicting earthquakes occurring in the region of Himalayan belt (with the use of different …

Analysis of 7-years Radon time series at Campi Flegrei area (Naples, Italy) using artificial neural network method

F Ambrosino, C Sabbarese, V Roca… - Applied Radiation and …, 2020 - Elsevier
This paper reports the analysis of soil 222 Rn data recorded over 7-years in the volcanic
caldera of Campi Flegrei (Naples-Italy). The relationship between Radon activity …