Issue |
MATEC Web Conf.
Volume 189, 2018
2018 2nd International Conference on Material Engineering and Advanced Manufacturing Technology (MEAMT 2018)
|
|
---|---|---|
Article Number | 11001 | |
Number of page(s) | 6 | |
Section | Semiconductor Applications | |
DOI | https://doi.org/10.1051/matecconf/201818911001 | |
Published online | 10 August 2018 |
A method of identifying and analyzing Outgoing Long-wave Radiation anomalies before earthquake
College of Mathematics and Informatics, Fujian Normal University, Fuzhou, 350000, China
*
Corresponding author : xzkong_fjnu@163.com
A large amount of anomalous information will appear before the earthquake, but it is difficult to identify and analyze valuable anomalous information from large-scale data. To solve this problem, this paper presents a method of pre-earthquake Outgoing Long-wave Radiation (OLR) anomaly identification and analysis based on quantum walking algorithm. The National Oceanic and Atmospheric Administration (NOAA) data are used to process and analyze the OLR data before and after the 6 major earthquakes in 2017 in western China.The results show that different degrees of thermal infrared anomalies have appeared before and after these large earthquakes. In this paper, we also analyze and discuss the similarities and differences of these changes by combining geological conditions and other factors.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.