DOI:
VOLUME 1 – OCTOBER ISSUE 3
Muhammad Akram*, David Pérez-Jorge, Momina Iftikhar, Sarvananda, Francisco Garcia-Sierra, Riyadh S Al-
Malki, Fethi Ahmet Ozdemir, Gawe? So?owski, Najmiatul Fitria, Marcos Altable, Adonis Sfera, Simone Brogi,
Ho Soonmin, Zaryab Fatima, El Hadji Seydou Mbaye, Isah Suleiman Yahaya, Md. Torequl Islam, Yahaya Usman
ABSTRACT
Understanding seismic activity patterns is necessary for earthquake behavior and
prediction in order to anticipate future earthquakes. Tectonic plate movement and
stress buildup along fault lines define seismic behavior. An examination of geological
features, historical earthquake data, and seismic activity monitoring are important
forecast techniques. While making exact forecasts is still difficult, advances in early
warning systems, machine learning, and real-time data analysis help us better assess
the danger of earthquakes and lessen their effects. In order to better understand and
anticipate seismic events, ongoing research combines theoretical frameworks with
observational data to improve preparedness and refine prediction models. It is
essential to comprehend earthquake behavior and forecast in order to reduce
seismic hazards and enhance safety. As a result of tectonic plate movements, stress
that has accumulated along geological faults is released during earthquakes.
Analyzing past earthquake data, geological traits, and patterns of seismic activity are
all part of predictive efforts. The methods used now include tracking seismic waves,
putting early warning systems in place, and using machine learning algorithms to
find probable antecedents. Because seismic processes are complicated, reliable
earthquake prediction remains elusive despite major progress. The objectives of
ongoing research are to increase prediction accuracy, incorporate real-time data,
and create practical mitigation plans that safeguard communities.
Keywords:
Geological Structures, Earthquake Precursors, Historical Earthquake
Data, Seismic Waves, Seismic Monitoring.