54 citations as recorded by crossref.

1. On the spatial scales of ionospheric perturbations caused by moderate earthquakes that occurred in Indian subcontinents K. Chaudhary et al. https://doi.org/10.1007/s12648-020-01992-0
2. Multi-station GPS-TEC Analysis of Pre-seismic Ionospheric Anomalies: The 2023 Kahramanmaras Earthquakes S. Karatay & F. Arıkan https://doi.org/10.21205/deufmd.2026288314
3. Thermal and TEC anomalies detection using an intelligent hybrid system around the time of the Saravan, Iran, (M= 7.7) earthquake of 16 April 2013 M. Akhoondzadeh https://doi.org/10.1016/j.asr.2013.12.017
4. TEC Anomalies Detection for Qinghai and Yunnan Earthquakes on 21 May 2021 Y. Yue et al. https://doi.org/10.3390/rs14174152
5. Support vector machines for TEC seismo-ionospheric anomalies detection M. Akhoondzadeh https://doi.org/10.5194/angeo-31-173-2013
6. Anomalous TEC variations associated with the strong Pakistan-Iran border region earthquake of 16 April 2013 at a low latitude station Agra, India D. Pundhir et al. https://doi.org/10.1016/j.asr.2013.11.012
7. Ionospheric effects of earthquakes in Japan in March 2011 obtained from observations of lightning electromagnetic radio signals V. Mullayarov et al. https://doi.org/10.5194/nhess-12-3181-2012
8. Firefly Algorithm in detection of TEC seismo-ionospheric anomalies M. Akhoondzadeh https://doi.org/10.1016/j.asr.2015.03.025
9. A multi-experiment approach to ascertain electromagnetic precursors of Nepal earthquakes S. Sharma et al. https://doi.org/10.1016/j.jastp.2019.105163
10. Investigating radon and TEC anomalies relative to earthquakes via AI models A. Muhammad et al. https://doi.org/10.1016/j.jastp.2023.106037
11. Ionospheric Disturbances Recorded by DEMETER Satellite over Active Volcanoes: From August 2004 to December 2010 J. Zlotnicki et al. https://doi.org/10.1155/2013/530865
12. TEC variations over the Mediterranean before and during the strong earthquake ( M = 6.5) of 12th October 2013 in Crete, Greece M. Contadakis et al. https://doi.org/10.1016/j.pce.2015.03.010
13. Seismogenic ionospheric anomalies associated with the strong Indonesian earthquake occurred on 11 April 2012 (M = 8.5) U. Pandey et al. https://doi.org/10.1016/j.asr.2017.12.022
14. Advances in Seismo-LAI anomalies detection within Google Earth Engine (GEE) cloud platform M. Akhoondzadeh https://doi.org/10.1016/j.asr.2022.03.033
15. Schumann resonance observation in China and anomalous disturbance possibly associated with Tohoku M9.0 earthquake X. Ouyang et al. https://doi.org/10.1007/s11589-013-0009-0
16. Earthquake prediction using satellite data: Advances and ahead challenges M. Akhoondzadeh https://doi.org/10.1016/j.asr.2024.06.054
17. A MLP neural network as an investigator of TEC time series to detect seismo-ionospheric anomalies M. Akhoondzadeh https://doi.org/10.1016/j.asr.2013.01.012
18. Ionospheric characteristics prior to the greatest earthquake in recorded history C. Villalobos et al. https://doi.org/10.1016/j.asr.2015.09.015
19. Study of ionospheric precursors using GPS and GIM-TEC data related to earthquakes occurred on 16 April and 24 September, 2013 in Pakistan region D. Pundhir et al. https://doi.org/10.1016/j.asr.2017.07.010
20. Two-stage modeling of ionospheric TEC for earthquake precursors: forecasting with LSTM, GRU, RNN and classification via Random Forest based on the 2023 Türkiye earthquakes C. Budak https://doi.org/10.1016/j.asr.2025.12.018
21. Statistical analysis of an ionospheric parameter as a base for earthquake prediction M. Li & M. Parrot https://doi.org/10.1002/jgra.50313
22. A Multi-Network based Hybrid LSTM model for ionospheric anomaly detection: A case study of the Mw 7.8 Nepal earthquake E. Şentürk et al. https://doi.org/10.1016/j.asr.2022.04.057
23. A review on remotely sensed land surface temperature anomaly as an earthquake precursor A. Bhardwaj et al. https://doi.org/10.1016/j.jag.2017.08.002
24. Remote Sensed Land Surface Temperature Anomalies for Earthquake Prediction M. Bellaoui et al. https://doi.org/10.4028/www.scientific.net/JERA.31.120
25. A New 3-D Error Diagram for a More Balanced Assessment of Binary Alarms for Predicting Earthquakes: Application to TIR Anomalies in Sichuan Area, China Z. Ying et al. https://doi.org/10.1109/TGRS.2023.3293132
26. Anomalous Variations of Ionosphere Associated with the Strong Earthquake at Pakistan-Iran Border at a Low Latitude Station Agra, India D. Pundhir et al. https://doi.org/10.1515/acgeo-2016-0020
27. Variations in the Power Spectral Density of Thunderstorm Discharge Pulses in the Frequency Band of 12–40 kHz Associated with Earthquakes in Japan and Taiwan V. Kabanov https://doi.org/10.1134/S0016793219010080
28. Atmospheric and ionospheric disturbances associated with the M > 6 earthquakes in the East Asian sector: A case study of two consecutive earthquakes in Taiwan M. Adil et al. https://doi.org/10.1016/j.jseaes.2021.104918
29. Ionospheric Whispers of the Earth’s Tremors: Decoding TEC Mysteries in the East Anatolian Fault Zone M. Ghafar et al. https://doi.org/10.1134/S0016793223600960
30. Impact of Geomagnetic Storms on Ionosphere Variability and Precise Point Positioning Application in High Latitudes of the Northern Hemisphereormalsize G. WANG et al. https://doi.org/10.11728/cjss2021.02.261
31. Sub-ionospheric very low frequency perturbations associated with the 12 May 2008 <i>M</i> = 7.9 Wenchuan earthquake A. Maurya et al. https://doi.org/10.5194/nhess-13-2331-2013
32. A semi-supervised total electron content anomaly detection method using LSTM-auto-encoder A. Muhammad & F. Külahcı https://doi.org/10.1016/j.jastp.2022.105979
33. Electromagnetic Emissions Recorded by a Borehole TOA Installment before Four Huge Destructive <i>M</i><sub>S</sub> ≥ 8.0 Earthquakes in Asia M. Li et al. https://doi.org/10.4236/ojer.2020.92004
34. On the significance of requisite criteria in detecting pre-earthquake ionospheric precursors: a case study of the Tohoku earthquake of March 11, 2011 V. Chukwuma et al. https://doi.org/10.1007/s11600-021-00627-0
35. Decision Tree, Bagging and Random Forest methods detect TEC seismo-ionospheric anomalies around the time of the Chile, (M= 8.8) earthquake of 27 February 2010 M. Akhoondzadeh https://doi.org/10.1016/j.asr.2016.03.035
36. GRIMS: global and regional ionosphere monitoring system B. Ozdemir et al. https://doi.org/10.1007/s10291-024-01702-x
37. Investigating short-term earthquake precursors detection through monitoring of total electron content variation in ionosphere N. Zulhamidi et al. https://doi.org/10.3389/fspas.2023.1166394
38. An Adaptive Network-based Fuzzy Inference System for the detection of thermal and TEC anomalies around the time of the Varzeghan, Iran, (M= 6.4) earthquake of 11 August 2012 M. Akhoondzadeh https://doi.org/10.1016/j.asr.2013.05.024
39. Pre-seismic anomalies in remotely sensed land surface temperature measurements: The case study of 2003 Boumerdes earthquake M. Bellaoui et al. https://doi.org/10.1016/j.asr.2017.03.004
40. Investigation of GPS-TEC measurements using ANN method indicating seismo-ionospheric anomalies around the time of the Chile (M= 8.2) earthquake of 01 April 2014 M. Akhoondzadeh https://doi.org/10.1016/j.asr.2014.07.013
41. Examination of seismo-ionospheric anomalies before earthquakes of Mw ≥ 5.1 for the period 2008–2015 in Oaxaca, Mexico using GPS-TEC A. Melgarejo-Morales et al. https://doi.org/10.1007/s11600-020-00470-9
42. Comparisons of autoregressive integrated moving average (ARIMA) and long short term memory (LSTM) network models for ionospheric anomalies detection: a study on Haiti (Mw = 7.0) earthquake M. Saqib et al. https://doi.org/10.1007/s40328-021-00371-3
43. Statistical Correlation Between DEMETER Satellite Electronic Perturbations and Global Earthquakes With M ≥ 4.8 Y. Zhang et al. https://doi.org/10.1109/TGRS.2023.3265931
44. Is the Apparent Correlation between Solar-Geomagnetic Activity and Occurrence of Powerful Earthquakes a Casual Artifact? M. Akhoondzadeh & A. De Santis https://doi.org/10.3390/atmos13071131
45. Kalman Filter, ANN-MLP, LSTM and ACO Methods Showing Anomalous GPS-TEC Variations Concerning Turkey’s Powerful Earthquake (6 February 2023) M. Akhoondzadeh https://doi.org/10.3390/rs15123061
46. A Review of Earthquake Precursor Anomaly Extraction Techniques for Geophysical Time-Series Observations Z. Yu et al. https://doi.org/10.1007/s10712-026-09927-w
47. Application of the T2-Hotelling test for investigating ionospheric anomalies before large earthquakes Z. Sadeghi & M. Mashhadi-Hossainali https://doi.org/10.1016/j.jastp.2019.01.010
48. Anomalous seismo-LAI variations potentially associated with the 2017 Mw = 7.3 Sarpol-e Zahab (Iran) earthquake from Swarm satellites, GPS-TEC and climatological data M. Akhoondzadeh et al. https://doi.org/10.1016/j.asr.2019.03.020
49. Developing a Deep Learning-Based Detector of Magnetic, Ne, Te and TEC Anomalies from Swarm Satellites: The Case of Mw 7.1 2021 Japan Earthquake M. Akhoondzadeh et al. https://doi.org/10.3390/rs14071582
50. Genetic algorithm for TEC seismo-ionospheric anomalies detection around the time of the Solomon (M= 8.0) earthquake of 06 February 2013 M. Akhoondzadeh https://doi.org/10.1016/j.asr.2013.04.012
51. Ionospheric anomalies detection using autoregressive integrated moving average (ARIMA) model as an earthquake precursor M. Saqib et al. https://doi.org/10.1007/s11600-021-00616-3
52. Identification of Seismogenic Anomalies Induced by 11 April, 2012 Indonesian Earthquake (M = 8.5) at Indian Latitudes Using GPS-TEC and ULF/VLF Measurements . Devbrat Pundhir et al. https://doi.org/10.1134/S0016793221030129
53. On the detection of anomalous seismo-ionospheric behavior in the presence of space weather stimuli for large earthquakes B. Lim & E. Leong https://doi.org/10.1016/j.asr.2018.10.020
54. Effect of Some Major Shallow Earthquakes (M > 6.0, Depth < 30 km) that Occurred in and Around India on the GPS-Based Total Electron Content (TEC) of the Ionosphere . Manish Awasthi et al. https://doi.org/10.1134/S0016793223600819