Research on the Standardized Management System and Operational Indicators of Water Control Dikes Based on GA-BP Artificial Neural Network Model
Round 1
Reviewer 1 Report
The paper entitled “Research on standardized management system and operational indicators of water control dyke based on GA-BP artificial neural network model” aims to establish an indicator-based assessment model for safe production in dykes, using Analytical Hierarchy Process (AHP) and GA-BP neural network based on the Matlab platform. Before giving my definitive approval to the article, I would like to ensure that the final text addresses the following remarks and suggestions:
Study Area Section: The authors omitted the section that provides information about the study area, both in the text and figures. It is essential to include this information to provide context and clarity to the readers. Please make sure that a comprehensive description of the study area is added.
Equation Numbering: It appears that the equation numbers are not indicated in the text. Proper equation numbering is crucial for reference and clarity. I kindly request that the equations be appropriately numbered in the manuscript.
Incorporation of New References: Please add the new references as suggested. It is essential to ensure that the article is up-to-date and reflects the latest relevant literature.
Once these revisions are made, and the final text reflects these changes, I would be pleased to consider the paper for acceptance. Your attention to these details will contribute to the quality and completeness of the article.
Minor editing of English language required
Author Response
The authors would like to express their gratitude to the Reviewer 1 for the valuable comments and suggestions. We acknowledge that the paper has been greatly improved by the helpful and useful comments and suggestions raised by the reviewer. Our responses to the reviewer’s comments are summarized in the following. In the revised version of the manuscript, we have highlighted the changes in yellow in the manuscript. Once again, many thanks for the reviewer’s time and supports.
(1) The authors have added the section that provides information about the study area, both in the text and figures. It is shown in Line 225 to Line 235.
(2) The equations have been appropriately numbered in the revised manuscript. Please check!
(3) The authors have added the new references. So that the article is up-to-date and reflects the latest relevant literature. It is shown in Line 133 to Line 151.
Reviewer 2 Report
Thank you for the opportunity to read the manuscript and please allow me to make a few suggestions for the authors.
Some technical terms and acronyms might be difficult for readers without a background in the field to understand. Therefore, I advise authors to define/explain a little bit more the acronyms and the terms used (especially those specific to Information Technology area), so as to introduce some of the readers who might have little background on neural networks, genetic algorithms, AHP etc.
The number of references that are quoted in the manuscripts seems rather small, I recommend the authors to try to reference further publications and studies from other authors for a more comprehensive background for the study.
Based on this, I recommend that the authors compare their own results with those from other authors in the Discussion and results section, and emphasize more their own contributions to the research field (versus those of the other authors).
I suggest that the authors try to present a little more details on the sample size and demographic to highlight more the representativeness of the sample.
I also suggest that the authors clarify a little bit more how the Excel spreadsheet was used in the study and how it contributed to the results.
Aren’t any limitations to this present study or potential sources of error? I was not able to find in the text something about the limitations and how to surpass them. For example, one limitation could be the use of method AHP for the data analysis, rather old, although there might be other methods that could be used (TOPSIS, SIMUS, SAW, PROMETHEE etc.). For example, in their future research the authors could approach more methods.
Another limitation might be that the authors focus only on engineering management of water resources through a case study in Jiangxi, China. Would it be possible to extend the study to other fields and/or even to other (larger) areas in the world?
I would also like to suggest that the authors could present at the end of the manuscript some ideas for continuing their research in the future.
Author Response
The authors would like to express their gratitude to the Reviewer 2 for the valuable comments and suggestions. We acknowledge that the paper has been greatly improved by the helpful and useful comments and suggestions raised by the reviewer. Our responses to the reviewer’s comments are summarized in the following. In the revised version of the manuscript, we have highlighted the changes in yellow in the manuscript. Once again, many thanks for the reviewer’s time and supports.
(1) The authors have explained a little bit more the acronyms and the terms used. AHP is explained in Line 256 to Line 264. BP and GA are explained in Line 311 to Line 334.
(2) The authors have referenced further publications and studies from other authors for a more comprehensive background for the study. The reference is shown in Line 735 to Line 756.
(3) The authors have compared their own results with those from other authors in Line 133 to Line 151. The authors have emphasized the own contributions to the research field in Line 182 to Line 212.
(4) The standardized management of water conservancy engineering is still in its infancy in China, and the working methods and technical requirements will continue to improve with the progress of the times. On the basis of absorbing advanced management experience, this project actively introduces advanced AHP comprehensive evaluation technology and neural network technology, forming its own unique standardized management evaluation method. Given the limited conditions, the results have not yet been widely applied, and the understanding of standardized management needs to be improved. In the future, we hope to conduct more in-depth research to make the results more reasonable and feasible. For example, standardized management of water conservancy engineering is a large-scale project that involves a wide range of aspects. How to better establish a standardized management system in our province on the basis of existing work achievements, provide a structurally sound, reasonable and feasible theoretical basis, is an effective measure to promote standardized management in a normalized manner. Establishing a more comprehensive and clear standardized management evaluation index system is an important content. Establishing a realistic evaluation model requires repeated practice and continuous improvement, which is a "learning" process. In the future, the achievements of standardized management in water conservancy engineering should be widely utilized to conduct multi-level and multi-angle research and evaluation of the effectiveness of this evaluation model. And we will actively try other methods that could be used (TOPSIS, SIMUS, SAW, PROMETHEE, etc.)
