93 citations as recorded by crossref.

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9. Multifractal analysis of three large earthquakes in Chile: Antofagasta 1995, Valparaiso 1985, and Maule 2010 D. Pastén & D. Comte https://doi.org/10.1007/s10950-014-9432-5
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30. Principle of Minimum Energy in Magnetic Reconnection in a Self-organized Critical Model for Solar Flares N. Farhang et al. https://doi.org/10.3847/1538-4357/aac01b
31. Analysis of aperture evolution in a rock joint using a complex network approach H. Ghaffari et al. https://doi.org/10.1016/j.ijrmms.2009.02.012
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33. Testing the structure of earthquake networks from multivariate time series of successive main shocks in Greece D. Chorozoglou et al. https://doi.org/10.1016/j.physa.2018.01.033
34. The network structure affects the fixation probability when it couples to the birth-death dynamics in finite population M. Dehghani et al. https://doi.org/10.1371/journal.pcbi.1009537
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46. Monofractal and multifractal analysis of the spatial distribution of earthquakes in the central zone of Chile D. Pastén et al. https://doi.org/10.1103/PhysRevE.84.066123
47. Time series analysis in earthquake complex networks D. Pastén et al. https://doi.org/10.1063/1.5023923
48. DYNAMICAL ANALYSES USING VISIBILITIES IN FINANCIAL MARKETS S. MIN et al. https://doi.org/10.1142/S0218348X1650016X
49. Avalanches on the complex network of Rigan earthquake M. Najafi et al. https://doi.org/10.1209/0295-5075/130/20001
50. Analyzing and modeling real-world phenomena with complex networks: a survey of applications L. Costa et al. https://doi.org/10.1080/00018732.2011.572452
51. Complex Network Study of Solar Magnetograms V. Muñoz & E. Flández https://doi.org/10.3390/e24060753
52. Landform classification based on landform geospatial structure – a case study on Loess Plateau of China S. Lin et al. https://doi.org/10.1080/17538947.2022.2088874
53. Investigating small-world and scale-free structure of earthquake networks in Greece D. Chorozoglou et al. https://doi.org/10.1016/j.chaos.2019.03.018
54. Automatic Landform Recognition from the Perspective of Watershed Spatial Structure Based on Digital Elevation Models S. Lin et al. https://doi.org/10.3390/rs13193926
55. Exploring watershed structural variation during watershed evolution process under artificial rainfall experiment S. Lin & N. Chen https://doi.org/10.1007/s12145-023-01000-z
56. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks G. Miranda et al. https://doi.org/10.1038/srep37329
57. Motifs in earthquake networks: Romania, Italy, United States of America, and Japan G. Pană & A. Nicolin-Żaczek https://doi.org/10.1016/j.physa.2023.129301
58. Small world picture of worldwide seismic events D. Ferreira et al. https://doi.org/10.1016/j.physa.2014.04.024
59. Let's get connected: A new graph theory‐based approach and toolbox for understanding braided river morphodynamics G. Connor‐Streich et al. https://doi.org/10.1002/wat2.1296
60. Dynamical mechanism of two meteorological factors in a complicated region S. Seo & K. Kim https://doi.org/10.3938/jkps.66.1611
61. From brain to earth and climate systems: Small-world interaction networks or not? S. Bialonski et al. https://doi.org/10.1063/1.3360561
62. The Solar Flare Complex Network A. Gheibi et al. https://doi.org/10.3847/1538-4357/aa8951
63. Natural Time Analysis of Seismicity within the Mexican Flat Slab before the M7.1 Earthquake on 19 September 2017 E. Flores-Márquez et al. https://doi.org/10.3390/e22070730
64. Seismic link at plate boundary F. Ramdani et al. https://doi.org/10.1007/s12040-015-0577-6
65. High-order synchronization of stick–slip process: experiments on spring–slider system T. Chelidze et al. https://doi.org/10.1007/s11071-009-9536-6
66. Complex earthquake networks: Hierarchical organization and assortative mixing S. Abe & N. Suzuki https://doi.org/10.1103/PhysRevE.74.026113
67. Multifractal time evolution for intraplate earthquakes recorded in southern Norway during 1980–2021 D. Pastén & C. Pavez-Orrego https://doi.org/10.1016/j.chaos.2022.113000
68. Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations W. Gregory et al. https://doi.org/10.5194/tc-16-1653-2022
69. Quantitative analysis and spatial distribution of landform spatial structure on Loess Plateau S. Lin et al. https://doi.org/10.1177/03091333221134192
70. Monitoring earthquake network measures between main shocks in Greece D. Chorozoglou & E. Papadimitriou https://doi.org/10.1007/s10950-019-09820-7
71. Cycle-flow–based module detection in directed recurrence networks R. Banisch & N. Djurdjevac Conrad https://doi.org/10.1209/0295-5075/108/68008
72. Unraveling Spurious Properties of Interaction Networks with Tailored Random Networks S. Bialonski et al. https://doi.org/10.1371/journal.pone.0022826
73. Time-Based Network Analysis Before and After the $$M_w$$ M w  8.3 Illapel Earthquake 2015 Chile D. Pastén et al. https://doi.org/10.1007/s00024-016-1335-7
74. Modeling the global ionospheric variations based on complex network S. Lu et al. https://doi.org/10.1016/j.jastp.2018.01.017
75. Global Dynamical Network of the Spatially Correlated Pc2 Wave Response for the 2015 St. Patrick's Day Storm S. Chaudhry et al. https://doi.org/10.1029/2022JA031175
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77. Contact temporal network during motility-induced phase separation I. Salas et al. https://doi.org/10.1103/t3k6-hcmr
78. A review on clustering algorithms for spatiotemporal seismicity analysis R. Vijay et al. https://doi.org/10.1007/s10462-025-11229-3
79. Analysis of topological properties in a seismic network W. Baek et al. https://doi.org/10.1016/j.physa.2011.11.047
80. Complex Networks and the b-Value Relationship Using the Degree Probability Distribution: The Case of Three Mega-Earthquakes in Chile in the Last Decade F. Martín & D. Pastén https://doi.org/10.3390/e24030337
81. Networks of Historical Contingency in Earth Surface Systems J. Phillips https://doi.org/10.1086/668557
82. Scale‐Free Structure of Surface‐Water Connectivity Within a Lowland River‐Floodplain Landscape C. Castillo et al. https://doi.org/10.1029/2020GL088378
83. Earthquake correlations and networks: A comparative study T. Krishna Mohan & P. Revathi https://doi.org/10.1103/PhysRevE.83.046109
84. A Prediction of Solar Cycle Maxima Using Visibility Graphs E. Flández & V. Muñoz https://doi.org/10.3847/1538-4357/adef43
85. Feature of topological properties in an earthquake network S. Min et al. https://doi.org/10.1016/j.physa.2015.08.062
86. Determination of the dynamical behavior of rainfalls by using a multifractal detrended fluctuation analysis S. Seo et al. https://doi.org/10.3938/jkps.61.658
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90. Spatiotemporal analysis of earthquake occurrence in synthetic and worldwide data D. Ferreira et al. https://doi.org/10.1016/j.chaos.2022.112814
91. Correlation Properties in Worldwide and Synthetic Earthquake Networks J. Ribeiro et al. https://doi.org/10.22564/brjg.v40i1.2134
92. Including dynamics in a network-based stochastic multihazard model: A virtual testbed for volcanic ashfall and flood risk assessment M. Bebbington et al. https://doi.org/10.1016/j.ijdrr.2025.105917
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