Earthquake magnitude prediction using a VMD-BP neural network model

Jiaqi Zhang and Xijun He ()
Additional contact information
Jiaqi Zhang: Beijing Technology and Business University (BTBU)
Xijun He: Beijing Technology and Business University (BTBU)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 117, issue 1, No 9, 189-205

Abstract: Abstract Earthquakes instantaneously occur and can cause huge disasters to cities, villages, and human beings. Therefore, it is of great significance to develop relevant theories and methods of earthquake prediction. This study builds a new model for seismic magnitude prediction, which uses a classic back propagation (BP) neural network combined with the variational mode decomposition (VMD) technique as a preprocessing for seismic dataset. The proposed model is referred to as VMD-BP. For each entry in the chronological earthquake catalog, three features are taken into consideration: magnitude, latitude, and longitude. The features of the past three adjacent seismic events are used as the input of the VMD-BP model, and the magnitude of the next seismic event is considered as the output. The VMD-BP model is then applied for seismic magnitude prediction in the Tibet and Yunnan regions. The results show that the VMD-BP model has high prediction accuracy, it performs better than the single BP neural network, and it can effectively predict the earthquake magnitude.

Keywords: Earthquake prediction; BP neural network; Variational mode decomposition; Earthquake magnitude (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-023-05856-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:117:y:2023:i:1:d:10.1007_s11069-023-05856-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-023-05856-8

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().