## 3 Results
Substituting the values into the Equation (2): \[d=2\times 6371\times\arcsin(\sqrt{0.000121+\cos(0.798)\times\cos(0.776)\times 0.000081})\cong 161.79\ \text{km}\]  
Based on the given coordinates, the distance from Vrancea to Bucharest is approximately 161.79 km. Equation (2) can be applied to any monitoring device in the report with an epicenter at Vrancea to determine its distance on the Earth's surface. Bucharest is 161 km from the Vrancea region. Considering this proximity, the equipment within this area is included in Equation (1) calculations about the Vrancea zone. In Figure 6, several locations within a 200 km radius of Vrancea are highlighted with a blue box, while three locations that exceed this distance are marked with a red box. Additionally, cities such as Pascani (162 km), Iasi (130 km), Piatra Neamt (96 km), Miercurea Ciuc (162 km), Buzau (141 km), Braila (178 km), and Calarasi (161 km) are located within a distance of less than 200 km from the Vrancea region. In contrast, Satu Mare (210 km), Giula (230 km), and Drobeta-Turnu Severin (220 km) exceed this imposed distance for analysis. Next, a C# script was developed to evaluate the model using the remaining 30% of the unseen data for the EMM model. The data are extracted using the following SQL query:  
_WITH MagnitudePositive AS ( SELECT Temperature, Pressure, Precipitation, Humidity, 1 AS MagnitudeIndicator, -- Column for Magnitude > 0 \(ROW\_NUMBER()\) OVER (ORDER BY NEWID()) AS RowNum FROM WeatherDataVrancea_  
_WHERE Magnitude > 0 ),  MagnitudeZero AS ( SELECT Temperature, Pressure, Precipitation, Humidity, 0 AS MagnitudeIndicator, -- Column for Magnitude = 0 \(ROW\_NUMBER()\) OVER (ORDER BY NEWID()) AS RowNum FROM WeatherDataVrancea_  
_WHERE Magnitude = 0 ) SELECT Temperature, Pressure, Precipitation, Humidity, MagnitudEndicator_  
_WHERE RowNum > (SELECT COUNT(*) * 0.7 FROM WeatherDataVrancea WHERE Magnitude > 0)  UNION ALL SELECT Temperature, Pressure, Precipitation, Humidity, MagnitudEndicator_  
_WHERE RowNum > (SELECT COUNT(*) * 0.7 FROM WeatherDataVrancea WHERE Magnitude = 0);_  
For testing purposes, a simulator was developed in C#. After executing the C# script on a dataset of 2606 values, an accuracy of 99.76% was achieved, with the EMM model correctly predicting 2600 of these values. It is important to note that the model was designed to provide a binary output, indicating not the magnitude of potential earthquakes but rather the probability of an earthquake occurring. Specifically, the model successfully identified 22 out of 23 actual earthquakes, demonstrating a high accuracy rate of 95.65% in earthquake detection. \[\phi_{1}=\frac{45.8\times\pi}{180}=0.798\ radians\]0 Examples of areas containing monitoring devices—Locations within 200 km of the Vrancea region (Blue: included location areas; Red: exceeding location areas). The same script calculated the EMM probability per Equation (1), considering data from 10 devices located within a 200 km radius of the Vrancea seismic center. Random values between 1 and 10 were generated for these ten devices to simulate their behavior in potential earthquake conditions. The values that indicate a possible earthquake event are particularly noteworthy, as presented in \[\phi_{1}=\frac{45.8\times\pi}{180}=0.798\ radians\]1  
The results in Table 5 demonstrate the earthquake event probability (\(P(EQ)\)) based on the EMM model and the number of devices reporting a possible event within a 200 km radius. With an initial event probability of 0.99, Table 5 shows varying levels of device reporting (ranging from 0.6 to 1). As expected, when more devices report a potential event (closer to 1), the predicted probability (\(P(EQ)\)) increases significantly, reaching as high as 0.993. When fewer devices report (e.g., 0.6), \(P(EQ)\) decreases to 0.873, showing that integrating device data influences the overall probability. The system operates within a standard range for acceleration, specifically between 98.73 and 98.96, after multiplying the raw values by 10.