77 citations as recorded by crossref.

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42. Incorporating Foreshocks in an Epidemic-like Description of Seismic Occurrence in Italy G. Petrillo & E. Lippiello https://doi.org/10.3390/app13084891
43. Forecasting induced seismicity in enhanced geothermal systems using machine learning: challenges and opportunities S. Karimpouli et al. https://doi.org/10.1093/gji/ggaf155
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45. Adaptive Declustering of Mining-Induced Microseismic Events and Cascading Triggering Behavior Under Deep Mining Conditions L. Dong et al. https://doi.org/10.1007/s00603-026-05841-0
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47. Aftershocks Identification and Classification G. Riga & P. Balocchi https://doi.org/10.4236/ojer.2017.63008
48. A Sustainable Monitoring and Predicting Method for Coal Failure Using Acoustic Emission Event Complex Networks Z. Zhang et al. https://doi.org/10.3390/su172411349
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54. Estimating the Epicenter of an Impending Strong Earthquake by Combining the Seismicity Order Parameter Variability Analysis with Earthquake Networks and Nowcasting: Application in the Eastern Mediterranean P. Varotsos et al. https://doi.org/10.3390/app112110093
55. Preparatory phase of large earthquakes illuminated by unsupervised categorization of earthquake catalog features S. Karimpouli et al. https://doi.org/10.1038/s41467-026-72279-x
56. The influence of the brittle-ductile transition zone on aftershock and foreshock occurrence G. Petrillo et al. https://doi.org/10.1038/s41467-020-16811-7
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62. A model of random walks on complex networks for earthquakes and aftershocks S. Upadhyay et al. https://doi.org/10.1016/j.chaos.2026.118846
63. Long-range correlation studies in deep earthquakes global series D. Ferreira et al. https://doi.org/10.1016/j.physa.2020.125146
64. Scaling and Clustering in Southern California Earthquake Sequences: Insights from Percolation Theory Z. Zhao et al. https://doi.org/10.3390/e27040347
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