10 citations as recorded by crossref.

1. Design of computationally efficient density-based clustering algorithms S. Nanda & G. Panda https://doi.org/10.1016/j.datak.2014.11.004
2. A multi-objective chimp optimization algorithm for seismicity de-clustering A. Sharma & S. Nanda https://doi.org/10.1016/j.asoc.2022.108742
3. 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
4. Strength-Pareto Based Multi-objective Adaptive Guided Differential Evolution Algorithm for De-clustering Seismic Catalogs A. Yadav et al. https://doi.org/10.1007/s44196-025-01091-0
5. A survey on nature inspired metaheuristic algorithms for partitional clustering S. Nanda & G. Panda https://doi.org/10.1016/j.swevo.2013.11.003
6. Tetra‐stage cluster identification model to analyse the seismic activities of Japan, Himalaya and Taiwan R. Vijay & S. Nanda https://doi.org/10.1049/iet-spr.2016.0639
7. Spatial-temporal seismicity analysis using TSOM and variational density peak clustering A. Sharma & S. Nanda https://doi.org/10.1007/s10651-024-00641-7
8. A review on clustering algorithms for spatiotemporal seismicity analysis R. Vijay et al. https://doi.org/10.1007/s10462-025-11229-3
9. 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
10. 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