## 2 Materials and Methods
### Data Import Process Description  
The data import process is designed to collect seismic and meteorological data corresponding to the Vrancea region of Romania, known for its seismic activity. This process employs two main data sources: earthquake data from the US Geological Survey (USGS) and weather data from the Open-Meteo API. The aim is to create a dataset that can facilitate the development of predictive models for earthquake forecasting:  
* Earthquake Data are obtained from the USGS API, which provides information regarding seismic events. The API allows users to filter earthquake records by specifying parameters such as date range, minimum magnitude, and geographical boundaries. For example, the query can be set to retrieve earthquakes with a magnitude of at least 2.5 within specific latitude and longitude constraints over a defined time frame. Multiple requests for API were made to retrieve data between 1 January 2001 and 5 October 2024. The temporal resolution of the earthquake data is daily, with each entry representing the magnitude of the highest-magnitude earthquake recorded on that particular day. This approach ensures that each earthquake event is captured as it happened. Days with no seismic events above magnitude 2.5 are recorded in the database with a magnitude value of 0. * Weather Data are sourced from the Open-Meteo API, which offers hourly records for several weather parameters. These parameters include precipitation, temperature, surface pressure, and relative humidity. These parameters will correlate with environmental conditions that may influence seismic activity. The API request can specify the geographical coordinates and the desired date range. Multiple requests were made to retrieve data for the same interval as for the earthquakes, and an average of the parameter values was computed for each day. While the meteorological data were initially available at an hourly resolution, the decision to aggregate these data into daily averages was made due to the improbability of an earthquake occurring immediately following an hourly-scale weather change. This approach reflects the assumption that significant weather-related influences on seismic activity would likely manifest over longer time spans rather than within a single hour. Thus, a daily temporal resolution was chosen to capture broader weather trends to earthquake occurrence better, avoiding unnecessary noise from short-term fluctuations and enhancing the model's predictive focus. The monitored parameters are as follows:* Precipitation measures the amount of rain, snow, sleet, or hail that falls over a specified period, expressed in millimeters (mm). Precipitation can influence geological processes, including the potential for seismic activity;
* Surface pressure is the ground-level atmospheric pressure measured in hectopascals (hPa). This parameter helps in analyzing the stability and movement of air masses. Changes in surface pressure can impact weather conditions, which may correlate with seismic events;
* The air temperature at 2 m indicates the temperature measured 2 m above the ground, expressed in degrees Celsius (\({}^{\circ}\)C). Temperature affects various environmental processes;
* Air relative humidity at 2 m is the percentage of moisture in the air compared to the maximum amount of moisture the air can hold at a given temperature. It is measured 2 m above ground level and expressed as a percentage (%). Relative humidity can influence atmospheric stability, which may indirectly affect seismic activity. The monitoring period is from 1 January 2001 to 5 October 2024. A total of 8766 records were analyzed for the development of the ML model. For each day within the monitored interval, the database will store the average values of the parameters provided. The relational SQL Server database contains a table that stores the abovementioned four parameters.