Firefly Algorithm in detection of TEC seismo-ionospheric anomalies. Issue 1 (1st July 2015)

• Record Type: Journal Article
• Authors: Akhoondzadeh, Mehdi
• Is Part Of: Advances in space research. Volume 56:Issue 1(2015)
• Page Start: 10
• Page End: 18
• Publication Date: 2015-07-01
• Subjects: Precursor -- Ionosphere -- TEC -- Anomaly; Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2015.03.025
• Languages: English
• ISSNs: 0273-1177

Abstract

Highlights: Firefly Algorithm detects TEC (Total Electron Content) seismo-ionospheric anomalies. Firefly Algorithm is based on the flashing patterns and behavior of fireflies. Multi-predictors analysis is effective in seismo-LAI precursor's studies. Abstract: Anomaly detection in time series of different earthquake precursors is an essential introduction to create an early warning system with an allowable uncertainty. Since these time series are more often non linear, complex and massive, therefore the applied predictor method should be able to detect the discord patterns from a large data in a short time. This study acknowledges Firefly Algorithm (FA) as a simple and robust predictor to detect the TEC (Total Electron Content) seismo-ionospheric anomalies around the time of the some powerful earthquakes including Chile (27 February 2010), Varzeghan (11 August 2012) and Saravan (16 April 2013). Outstanding anomalies were observed 7 and 5 days before the Chile and Varzeghan earthquakes, respectively and also 3 and 8 days prior to the Saravan earthquake.