Assessing the Influence of Seismic Parameters on Ground Motion Intensity: A Data-Driven Approach

This study investigates the significance and correlations of key seismic parameters, including magnitude, peak ground acceleration (PGA), peak ground velocity (PGV), and VS۳۰, which are crucial for predicting structural responses and enhancing seismic resilience. The research addresses common misunderstandings regarding the relationship between these parameters and ground motion intensity, which can lead to inaccurate analyses and design decisions. This study explores the significance of these parameters and their correlations, offering insights into ground motion characteristics and seismic behavior. To aid this analysis, a data processing application has been developed that efficiently handles essential tasks like data processing and conducting advanced machine learning and feature analysis. The application’s features include heatmap visualizations for correlation analysis and machine learning-based assessments of feature importance. These functionalities emphasize the importance of analyzing interdependencies among seismic parameters and demonstrate how such relationships influence our understanding of ground motion intensity

کلیدواژه ها:

Seismic Parameters ، Machine Learning ، Data Analysis