## 6 Conclusions  
In this study, we present the efficiency of our clustering method, MAP-DBSCAN, on a simulated earthquake catalog where the structure of the clusters is known a priori and its competitiveness against well-known clustering algorithms, as in most cases, shows better results. The main seismic clusters in the Corinth Gulf, Central Ionian Islands and North Aegean Sea during 2012-2019 are detected by our method and their clustering properties are investigated. The results show the existence of regional variability in aftershock productivity and background rates. In particular, the Corinth Gulf is characterized by low productivity values and high background rates related to the dominance of earthquake swarms, whereas seismicity in the Central Ionian Islands is comprised by main shock-aftershock sequences with high productivity. Sequence-specific parameters verify the dependence between low productivity values and high background rates with pore-pressure due to fluids migration. We believe that future studies on Operational Earthquake Forecasting should incorporate localized parameters into the models to improve the forecasting accuracy. **Supplementary Materials:** The following are available online at [[https://www.mdpi.com/article/10.3390/app12041908/s1](https://www.mdpi.com/article/10.3390/app12041908/s1)]([https://www.mdpi.com/article/10.3390/app12041908/s1](https://www.mdpi.com/article/10.3390/app12041908/s1)), Figure S1a-c Residuals (purple triangles) as a function of minimum cutoff magnitude, \(M_{c}\), for the D1, D2 and D3 datasets, respectively. Blue and cyan dotted horizontal lines indicate the 10% and 5% residual thresholds, respectively. \(M_{c}\) (red triangle) is found as the first magnitude cutoff at which the confidence 95% is reached. (d-f) Incremental (red triangles) and logarithmic cumulative frequency (blue triangles) as a function of magnitude. The black line is the GR law fit according to the GFT method with \(M_{c}=1.5\), \(2.2\), \(2.1\) for datasets D1, D2 and D3, respectively. Figure S2 (a) Epicentral map of the main seismic clusters during the first semester of 2012. Three major clusters, C1, C2 and C3, and eight smaller clusters with \(N\geq 10\) events occurred. (b) Space-time evolution of seismicity. Colors correspond to different clusters and the size of circles is proportional to the earthquakes' magnitude, Figure S3 (a) Epicentral map of the 2013 Aigion swarm and subsequent sequences in the area with \(N\geq 10\) events. (b) Space-time evolution of seismicity. Colours correspond to different clusters and the size of circles is proportional to the earthquakes' magnitude, Figure S4 (a)  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline
**ID** & \(T_{in}\) & \(T_{end}\) & \(N\) & \(p\) & \(c\) & \(b\) & \(a\) & K & \  
Epicentral map of the seismic activity between November, 2013 and June, 2014. Twelve clusters with \(N\geq 10\) occurred, including the C11, C12 and C14 clusters. (b) Space-time evolution of seismicity. Colors correspond to different clusters and the size of circles is proportional to the earthquakes' magnitude, Figure S5 (a) Epicentral map of the intense seismic activity during the second half of 2014. Five major clusters occurred, the C15, C16, C18, C19 and C20, and four smaller clusters with \(N\geq 10\) events. (b) Space-time evolution of seismicity. Colors correspond to different clusters and the size of circles is proportional to the earthquakes' magnitude, Figure S6 (a) Epicentral map of the seismic sequence Offish. Perichora. One major cluster, C4, including two sub sequences, the first initiated on 22 September and the second on 30 September, 2012. b) Space-time evolution of seismicity. Colours correspond to different clusters and the size of circles is proportional to the earthquakes' magnitude, Figure S7 (a) Epicentral map of the seismic activity near Itea Gulf during 2014. Two major clusters are occurred, the C13, C17 and four smaller ones with \(N\geq 10\) events. (b) Space-time evolution of seismicity.