27 citations as recorded by crossref.

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3. A many objective chimp optimization algorithm to de-cluster earthquake catalogs in space time domain A. Sharma & S. Nanda https://doi.org/10.1007/s00500-023-09314-2
4. 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
5. Memory guided Aquila optimization algorithm with controlled search mechanism for seismicity analysis of earthquake prone regions A. Sharma & S. Nanda https://doi.org/10.1016/j.asoc.2023.110894
6. Premonitory Earthquakes Clustering Process in an Equivalent Dimensions Space before the 2017 Mw 8.2 Tehuantepec, Mexico, Mainshock S. Lasocki et al. https://doi.org/10.1785/0220240026
7. A review on clustering algorithms for spatiotemporal seismicity analysis R. Vijay et al. https://doi.org/10.1007/s10462-025-11229-3
8. A tentative model for the explanation of Båth law using the order parameter of seismicity in natural time K. Papadopoulou et al. https://doi.org/10.1007/s11589-016-0171-2
9. Identification and spatio-temporal analysis of earthquake clusters using SOM–DBSCAN model A. Sharma et al. https://doi.org/10.1007/s00521-022-08085-5
10. Hidden-state modeling of a cross-section of geoelectric time series data can provide reliable intermediate-term probabilistic earthquake forecasting in Taiwan H. Wen et al. https://doi.org/10.5194/nhess-22-1931-2022
11. Comparing spatio-temporal networks of intermittent avalanche events: Experiment, model, and empirical data D. Biton et al. https://doi.org/10.1016/j.chaos.2019.109519
12. Clustering regimes in a sandpile with targeted triggering R. Batac https://doi.org/10.1209/0295-5075/135/19003
13. Micro-scale, mid-scale, and macro-scale in global seismicity identified by empirical mode decomposition and their multifractal characteristics N. Sarlis et al. https://doi.org/10.1038/s41598-018-27567-y
14. A spatio-temporal binary grid-based clustering model for seismicity analysis R. Vijay et al. https://doi.org/10.1007/s10044-024-01234-7
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16. Statistical Properties of the Immediate Aftershocks of the 15 October 2013 Magnitude 7.1 Earthquake in Bohol, Philippines R. Batac https://doi.org/10.1515/acgeo-2015-0054
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18. A Quantum Grey Wolf Optimizer based declustering model for analysis of earthquake catalogs in an ergodic framework R. Vijay & S. Nanda https://doi.org/10.1016/j.jocs.2019.07.006
19. The role of intervention mechanisms on a self-organized system: dynamics of a sandpile with site reinforcement P. Sy & R. Batac https://doi.org/10.1088/2632-072X/ad28ff
20. Spatiotemporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest‐neighbor approach V. Vasylkivska & N. Huerta https://doi.org/10.1002/2016JB013918
21. On the nature and dynamics of the seismogenetic systems of North California, USA: An analysis based on Non-Extensive Statistical Physics A. Efstathiou et al. https://doi.org/10.1016/j.pepi.2017.06.010
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23. Sandpile-based model for capturing magnitude distributions and spatiotemporal clustering and separation in regional earthquakes R. Batac et al. https://doi.org/10.5194/npg-24-179-2017
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25. Scaling laws in earthquake memory for interevent times and distances Y. Zhang et al. https://doi.org/10.1103/PhysRevResearch.2.013264
26. Tsallis q-Statistics in Seismology L. Sigalotti et al. https://doi.org/10.3390/e25030408
27. Earthquake occurrences in the Pacific Ring of Fire exhibit a collective stochastic memory for magnitudes, depths, and relative distances of events P. Roque et al. https://doi.org/10.1016/j.physa.2024.129569