• Rahmathunnisa
• Dr. Harish B G
• Chetan Kumar G S
• Sadiya Anjum
• Pavan U R

This project proposes the use of a linear regression model for earthquake prediction by analyzing seismic data. The model captures the linear relationship between input features and earthquake occurrences, such as magnitude, depth, and location. The dataset is preprocessed, split into training and testing sets, and the model is trained using gradient descent. Evaluation metrics demonstrate the model's strong correlation and accurate estimation of earthquake probabilities. The simplicity and interpretability of the linear regression model make it practical for implementation and decision-making in earthquake prediction. Further research can explore additional features and compare it with other machine learning algorithms for improved accuracy.

Machine Learning (ML), Machine Technique.

"Earthquake Prediction Model Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.i444-i448, July-2023, Available :http://www.jetir.org/papers/JETIR2307861.pdf

"Earthquake Prediction Model Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppi444-i448, July-2023, Available at : http://www.jetir.org/papers/JETIR2307861.pdf