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Article
Peer-Review Record

Assessment of the Rock Elasticity Modulus Using Four Hybrid RF Models: A Combination of Data-Driven and Soft Techniques

Appl. Sci. 2023, 13(4), 2373; https://doi.org/10.3390/app13042373
by Chuanqi Li and Daniel Dias *
Reviewer 1:
Reviewer 2:
Reviewer 3:
Appl. Sci. 2023, 13(4), 2373; https://doi.org/10.3390/app13042373
Submission received: 7 January 2023 / Revised: 10 February 2023 / Accepted: 10 February 2023 / Published: 12 February 2023
(This article belongs to the Special Issue The Application of Machine Learning in Geotechnical Engineering)

Round 1

Reviewer 1 Report

Table 1 should not add in the introduction, I think it should me graphical form rather than tabular.

Data presentation part should be in result section

 

There is lack of quality work in reference , it should be reduced and cite only most related and quality articles

Author Response

Dear colleague,

Please find our answers in the attached file,

Cordially,

Daniel

Author Response File: Author Response.docx

Reviewer 2 Report

The article is about estimating the modulus of elasticity using machine learning hybrid models. The authors combined four optimization methods with the Random Forest model to optimize the hyperparameters of the model (number of trees and max depth). The notes to the article are as follows:

1. English editing by a native speaker is highly recommended. Authors sometimes use capital letters in the names in an incomprehensible way, e.g. "geotechnical engineering" or "American standards for testing materials". Apart from that there are a lot of typos.

2. I am asking for a deeper explanation of why and how the authors chose the predictors for modeling. The authors give four variables adopted for the analysis and try to explain them with generally used empirical formulas. I see a bit of a methodological error here. Why did the authors not include other parameters, such as the uniaxial compression strength of the sample? Based on this value, Young's modulus can also be determined. Unfortunately, I also miss the analysis of independent variables. Correlation analysis alone may not necessarily provide a sufficient answer that the assumed variables are correct. A more in-depth analysis should be carried out, taking into account a greater number of predictors and, for example, their elimination in order to obtain the final number of dependent variables.

3. What is the RM model?

Author Response

Dear colleague,

Please find our answers in the attached file,

Cordially,

Daniel

Author Response File: Author Response.docx

Reviewer 3 Report

This paper compares four effective hybrid RF models to predict the rock EM. The paper is well organized and well written. I just only have one minor comment for authors. I suggest that authors should clearly explain what correlation analyses is and how it is carried out in section 2. Figure 1 is also needed to be explained. So, I can suggest the paper for publication.    

 

 

Author Response

Dear colleague,

Please find our answers in the attached file,

Cordially,

Daniel

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The authors responded appropriately to the comments of the reviewers and made corrections

Author Response

Thanks for your revision

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