Automatic detection of internal wave using particle swarm optimization algorithm

9th IGRSM International Conference and Exhibition on Geospatial & Remote Sensing

地球科学;计算机科学

Marghany, Maged^1,2

Geography Section, Faculty of Humanities, Universiti Sains Malaysia, Penang, Malaysia^1

Faculty Geospatial and Real Estate, Geomatica University College, Kuala Lumpur, Malaysia^2

关键词: 2-D wavelet transform;    Automatic Detection;    Internal waves;    Normalized radar cross section;    Optimization algorithms;    Particle swarm;    Particle swarm optimization algorithm;    Radar backscatter;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/169/1/012049/pdf
DOI  :  10.1088/1755-1315/169/1/012049

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The work demonstrated a new approach for internal wave automatic detection during 2004 tsunami. In this regard, optimization algorithm of Particle Swarm is used with 2-D wavelet transform of ASAR satellite data. It indicates the regulated radar backscatter ranged between -4 to -24 dB. The lowest normalized radar cross section of -28dB is described the low window quarter shelter alongside the Andaman and Nicobar Islands. Nevertheless, the maximum backscatter of -4 dB is pronounced the prevalence of whirlpool in the east of the Andaman Sea. The whirlpool has a radius of 1.9 km which is estimated using optimization algorithm of Particle Swarm. This whirlpool is located above of water depth gradient of 1000 m. In conclusion, the Particle Swarm Optimization has routinely realize internal wave which generated by the 2004 tsunami.