Estimation of Uncertainty for Technology Evaluation Factors via Bayesian Neural Networks

Round 1

Reviewer 1 Report

The paper "Estimation of Uncertainty for Technology Evaluation Factors via Bayesian Neural Networks" is interesting paper, but the authors should address the following concerns:

1. The article should be checked in terms of English and grammatical errors should be fixed.

2. The innovations of the article should be briefly stated in the abstract.

3. Use new articles, especially 2022-2023, to express the issue and the importance of the issue. Please move on the edge of knowledge

4. Innovations and contributions should be described in the introduction. What is the novelty of your study?

5. Research literature is old. Please use the new articles for 2022-2023 and move on to the edge of knowledge.

6. The validation of the results is not seen in the article, the authors should add the validation of the results in the article.

 

7. In Conclusions, the limitations of the research should be stated first, and then suggestions for future research should be presented based on the limitations of the research.

Author Response

We have incorporated your advice into the manuscript.

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

This study aims to estimate uncertainties of the factors that are frequently used in technology-based studies. Although this topic is of interest, there are still some problems. The following suggestions are helpful to further improve the quality of this paper.

 

Q1: Enrich the abstract. Briefly describe the motivation and improvement of the methods used in the paper.

Q2: Elaborate the motivation by items in the introduction. Motivation for induction papers and improvement of the problem.

Q3: Please add BNN's Framework Diagram to better represent your approach.

Q4: Figure 3, please add the data labels.

Q5: The comparison of model accuracy between LR and BNN is not much different in Figure 3, but NBB’s model is our innovation point, please make a reasonable explanation.

Q6: The values of the f-measure in Figure 3 are close to each other, and the improvement  highlighted in the paper is not very big, For example “Prediction reduce the time and cost”.please give a reasonable explanation.

Q7: Please explain Figure 5 in more detail.

Q8: Too little description of future work.

Q9: Section 6 discusses several limitations of your study, and the limitations of the method are also presented in Section 7. Please make adjustments for this issue.

Author Response

We have incorporated your advice into the manuscript.

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The authors answered the questions and the article is suitable for publication.

Author Response

Thank you for your hard work.

Also, thanks to your detail advice, the quality of our manuscript has been improved.