Explainable and statistically validated machine learning for earthquake alert-level classification using seismic intensity features

Predicting Seismic Intensity Using Machine Learning With Ancillary Data: Evidence From Destructive Earthquakes in China

Accurate and rapid assessment of seismic intensity is crucial for postearthquake emergency response. This is especially true during the initial “black‐box” period, when real‐time data are scarce. To address this challenge, we developed a machine learning‐based (ML) framework for predicting kilometer‐grid‐scale seismic...

Enhancing Earthquake Prediction using Machine Learning with Optimization Method

Earthquakes have complex seismic characteristics that make accurate classification challenging. This study proposes a machine learning approach that combines K-Means clustering and Random Forest to improve earthquake classification performance. We utilize earthquake records with numerical and geographic attributes, inc...

Earthquake Damage Risk Classification Using Machine Learning Models Based on Built-Up Area Indices from Satellite Imagery

One of the challenges in assessing earthquake damage risk in areas with high seismic activity and limited data is the lack of a detailed building inventory and the absence of available data. Therefore, a remote sensing and machine learning framework is needed that can utilize the built-up area index with NDBI from mult...

Event-Wise Validation of Machine Learning for Magnitude-Threshold Classification Using the Turkish Strong-Motion Database (SMD-TR)

Magnitude-threshold classifiers trained on multiple station records from the same earthquake are vulnerable to event-level data leakage, and comparisons across magnitude boundaries can be misleading because the class definition and prevalence change. We evaluated ten machine-learning classifiers using the official SMD-...

A Real-Time Seismic Intensity Prediction Framework Based on Machine Learning for Earthquake Early Warning

Machine Learning–based Earthquake Probability Prediction for Istanbul Province

Earthquakes represent one of the most destructive natural hazards, causing severe social and economic losses, particularly in tectonically active regions. In this context, estimating the short-term probability of earthquake occurrence is of critical importance for disaster preparedness and risk mitigation. This study f...