Next Article in Journal
Integrating a LiDAR Sensor in a UAV Platform to Obtain a Georeferenced Point Cloud
Previous Article in Journal
The Influence of Processing Time on Morphology, Structure and Functional Properties of PEO Coatings on AZ63 Magnesium Alloy
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 12
Issue 24
10.3390/app122412849
Review Report
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
Article
Peer-Review Record

An Earthquake Early Warning Method Based on Bayesian Inference

Appl. Sci. 2022, 12(24), 12849; https://doi.org/10.3390/app122412849
by Jingsong Yang 1,2, Fulin He 1, Zhitao Li 3,* and Yinzhe Zhang 1
Reviewer 1: Anonymous
Reviewer 2:
Andrzej Kijko
Appl. Sci. 2022, 12(24), 12849; https://doi.org/10.3390/app122412849
Submission received: 6 November 2022 / Revised: 6 December 2022 / Accepted: 9 December 2022 / Published: 14 December 2022
(This article belongs to the Special Issue Earthquake Early Warning System: Science and Technology, Challenges and Limitations)

Round 1

Reviewer 1 Report

The manuscript “An earthquake early warning method based on a Bayesian theory” investigate an earthquake magnitude and peak ground velocity (PGV) identification method based on application of Bayes-theorem on Guttenberg-Richter relationship. The authors introduce the proposed and the reference (traditional) methodology and show their application on the seismic dataset in Japan provided by the Japan national research institute for earth science and disaster prevention. The provided results show the higher accuracy of the introduced method in comparison to the traditional method.

The presented results are scientifically interesting and fit into the scopes of the journal. Nevertheless, I have several remarks, in particular, concerning the appearance of the manuscript.

Remarks

L. 28: P-wave: primary or pressure?

L. 42: Pa and Pv not defined.

Fig. 1 and others. The quality / resolution seems to be low. In addition, the fontsize could be increased.

L. 93-94: The explanation “Standard deviation of the equation (5)” is not clear. Probably std. of a(ti) in eq. (5)

L. 106: “ti” instead of “ti”. Last appearance of a(ti) should be probably v(ti).

L. 124: “data as likelihood” should be explained more detailed.

L. 139: “time x”

L. 146 / eq. (11). The appearance of mu is not clear.

L. 150 / eq. (12). The appearance of mu is not clear.

L. 167-168. Expectation and std of which quantity?

L. 171 “, The”.

L. 160: “Both the bayesian” instead of “both the Bayesian”.

Author Response

I have made some revisions and replies to your review comments. The contents are in the document below, please check.

Author Response File: Author Response.docx

Reviewer 2 Report

The reviewed manuscript has the potential to contribute to the difficult problem of establishing an efficient early warning system for earthquake occurrence. The only problem I have with the reviewed manuscript is its language. It is clear to me that the text was translated. Unfortunately, the person translating the original manus is not familiar with seismological terms. For example, in seismology, we are not saying "speed" but rather "velocity" (ground velocity). Also,  instead of using the term "Bayesian theory", I would suggest replacing it with "Bayesian formalism", "Bayesian methods", or "Bayesian inference".  Of course, there are small and insignificant problems. After language correction by English spoken seismologist, I believe the manus will be suitable for publishing.  

Author Response

I have made some revisions and replies to your review comments. The contents are in the document below, please check.

Author Response File: Author Response.docx

Back to TopTop