Review Reports
- Xiaosheng Chuai1,2,3,*,
- Longyong Shu2,* and
- Zhonggang Huo2
- et al.
Reviewer 1: Onur Dogan Reviewer 2: Oksana Mulesa Reviewer 3: Anonymous
Round 1
Reviewer 1 Report
Comments and Suggestions for Authorsattached
Comments for author File: 
Comments.pdf
Author Response
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Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe manuscript is devoted to the prediction of rockburst. The topic is relevant, as it addresses a serious engineering problem in underground mining and tunneling. The issue of prediction has been widely covered in the contemporary scientific literature. The use of a combined methodology of Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation allows considering multiple factors and reducing subjectivity, which adds certain novelty.
The scientific contribution lies in the combination of AHP for the justified determination of index weights and fuzzy logic for the comprehensive evaluation. Although the authors claim that the AHP–Fuzzy method has rarely been applied to rockburst prediction, its applications in other engineering fields are well known. Therefore, the level of innovativeness appears limited, as the paper focuses more on adaptation rather than on a fundamentally new theoretical framework.
The literature review is very detailed: the authors analyzed more than 60 different methods. While this is a strength of the study, the review itself appears overly lengthy and sometimes repeats well-established statements without critical synthesis. It would be advisable to structure the review by groups of methods, with a clearer comparison of their advantages and limitations.
A strength of the study is the transparency of the algorithms. However, the choice of exactly eight indices has not been sufficiently justified.
The experimental verification shows that the model identifies gradations from “no rockburst” to “strong rockburst” with a sufficiently logical distribution. However, the validation is limited to a single case study, and the authors do not provide a comparison of accuracy with other models, nor do they include statistical validation.
The text contains grammatical errors.
Recommendations to the authors are as follows:
The English language of the manuscript requires serious editing.
The literature review should be restructured and made more concise.
The choice of the selected indices needs to be justified.
To confirm the universality of the model, results from other case studies should be presented, or at least a comparison with existing models should be provided.
Quantitative performance metrics (e.g., accuracy, precision, recall, F-score) should be added to evaluate the effectiveness of the model.
The conclusions mostly repeat the results; they should be strengthened by clearly outlining the unique contribution of the work, its limitations, and possible directions for future research.
The terminology should be unified throughout the text.
The formulas need to be reformatted, as there are certain issues with readability and interpretation.
Comments on the Quality of English LanguageThe English language of the manuscript requires substantial improvement.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe paper titled “Analytical Hierarchy Process Fuzzy Comprehensive Evaluation Model for Predicting Rockburst with Multi-Indexes” is well-structured, and the authors have clearly explained the significance of the research topic.
The contributions of this work lie in the integration of the AHP method with FCE for predicting rockbursts. The paper offers a somewhat limited theoretical contribution in the domain of decision-making and risk assessment, while providing a stronger practical contribution in the field of Geotechnical Engineering and Rock Mechanics/Engineering.
As I noted, the methodological contribution of the paper is relatively modest. Therefore, attention should be given to the following aspects:
(1) The authors emphasize that expert assessments are overly subjective and therefore rely on the classical AHP method. I believe it would be highly valuable for readers to understand why the Fuzzy AHP (FAHP) approach was not used.
(2) I could not identify who evaluates the values in the pairwise comparison matrix. Readers are left without this important information. It is implied that a single person conducts the evaluation. However, questions arise regarding who this person is, their qualifications for making such assessments, whether it is necessary to involve multiple decision-makers (experts), etc. How reliable is it to use the evaluation of a single individual as a general indicator?
(3) The FCE approach was used. Could any MADM method be employed for this purpose, for instance, a well-established method such as TOPSIS or a newer approach like RADAR? Could these methods be extended using fuzzy set theory and applied in this case?
My recommendation is major revisions
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsAcceptable in the present form
Author Response
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Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsMost of the recommendations have been taken into account by the authors. The work is correct and has practical value. I recommend paying attention to the following remarks:
- Add performance indicators of the model.
- Present the obtained results for other objects or summarize why this case is representative.
- Specify the scientific contribution more clearly.
- Expand the conclusions with information about the limitations of the model’s application, prospects for further research, etc.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors have adequately addressed the reviewer’s comments. I recommend the manuscript for acceptance.
Author Response
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Author Response File: Author Response.pdf