• Sakshi Bhatt
• Syed Naashit Hashmi
• Sandeep Kumar

Earthquakes are defined as sudden, violent shaking of the surface of the Earth caused by transitory energy from all of the planet's major structures. These waves are created when energy stored throughout the earth's crust is released suddenly, usually when large amounts of rock are merely restraining next to one another split, and slip [26]. An earthquake is responsible for threatening people, their homes, and the whole infrastructure [24]. Traditional methods couldn't provide real-time information about earthquakes, but now, with the help of machine learning and deep learning, we are getting much better at it. We have many sensors and instruments that collect data about things like ground movements, geological observations, and measurements of the Earth. Machine learning and deep learning are powerful tools that help us make sense of all this data. In this study, we focus on the forward Neural Network. FFNN is excellent at understanding the patterns and changes in earthquake data over time, making it great for time-series data. So, by using this advanced model, we're getting better at understanding and predicting earthquakes, which is incredibly important for safety and preparedness. It's like having a more accurate earthquake warning system to keep people safe.

Earthquake Prediction, Machine Learning, Deep Learning, Seismic Data, Real- Time Monitoring Sensors, Geological Observations, Data Analysis, Feed Forward Neural Network, Safety Preparedness, Early Warning System, Geospatial Analysis, Time-Series Data

"Advancements in Earthquake Forecasting Using Feedforward Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.f129-f137, April-2024, Available :http://www.jetir.org/papers/JETIR2404516.pdf

"Advancements in Earthquake Forecasting Using Feedforward Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppf129-f137, April-2024, Available at : http://www.jetir.org/papers/JETIR2404516.pdf