An approach in Prediction of Earthquakes using VAE-LSTM model

Karyamapudi, Suraj (2023) An approach in Prediction of Earthquakes using VAE-LSTM model. Masters thesis, Dublin, National College of Ireland.

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Abstract

Earthquakes are one of the most devastating natural disasters, resulting in significant loss of life and property. Early detection can aid in the timely evacuation of affected areas, reducing the potential damage. While traditional methods of earthquake detection and prediction have seen advancements, there remains room for improved accuracy and timeliness. This research leverages the capabilities of Variational Autoencoders (VAE) combined with Long Short-Term Memory (LSTM) networks to create a model designed for real-time earthquake detection.A novel approach was adopted by integrating VAE with LSTM to process seismic data, aiming to predict potential earthquake occurrences.The VAE-LSTM model demonstrated improved accuracy and efficiency in detecting seismic activities compared to conventional methods.The integration of VAE and LSTM offers a promising direction in the realm of seismology, indicating the potential of deep learning models in understanding and predicting complex natural events.The VAE-LSTM model can be deployed in seismic monitoring stations worldwide, offering more accurate, timely warnings that can save lives.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Shahid, Abdul UNSPECIFIED
Uncontrolled Keywords:	VAE-LSTM; LSTM; Machine Learning; Earthquake
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science G Geography. Anthropology. Recreation > GE Environmental Sciences > Earth sciences > Geology > Physical geology > Sedimentation and deposition > Earth movements > Earthquakes Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	25 Nov 2024 14:04
Last Modified:	26 Nov 2024 11:25
URI:	https://norma.ncirl.ie/id/eprint/7196

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