A Source Seeking Method for the Implicit Information Field Based on a Balanced Searching Strategy
Round 1
Reviewer 1 Report
This paper presents a source seeking method for the implicit information field based on a balanced searching strategy. Generally speaking, this paper is well-written and clear. There are some publishable contents in this paper. However, the following comments should be considered:
Comments:
1. The motivation of this paper should be further strengthened and the main contributions should be pointed out.
2. The language quality of the paper is good bud needs to be polished further
3. The authors could add a remark to discuss the novelty and advantages of the proposed work.
4. What are the limitations of the proposed work? Give a note on it.
5. The authors could provide more discussion on the simulation results.
The language quality of the paper should be improved further.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
1. The manuscript is concerned with a source seeking method for the implicit information field based on a balanced searching strategy, which is interesting. It is relevant and within the scope of the journal.
2. However, the manuscript, in its present form, contains several weaknesses. Adequate revisions to the following points should be undertaken in order to justify recommendation for publication.
3. For readers to quickly catch the contribution in this work, it would be better to highlight major difficulties and challenges, and your original achievements to overcome them, in a clearer way in abstract and introduction.
4. p.1 - an autonomous souring method based on balanced searching strategy is adopted to solve the problem of low efficiency of source seeking in implicit information field. What are the advantages of adopting this method over others in this case? How will this affect the results? More details should be furnished.
5. p.1 - the distribution entropy is adopted to measure the searching bias in the process of source seeking. What are the other feasible alternatives? What are the advantages of adopting this approach over others in this case? How will this affect the results? More details should be furnished.
6. p.9 - the schematic diagram as shown in Figure 5 is adopted for the decomposition in source searching stage. What are other feasible alternatives? What are the advantages of adopting this framework over others in this case? How will this affect the results? The authors should provide more details on this.
7. p.11 - geomagnetic field is adopted in the experiments. What are other feasible alternatives? What are the advantages of adopting this field over others in this case? How will this affect the results? The authors should provide more details on this.
8. p.11 - specific parameter setting are adopted for carrier movement. What are the other feasible alternatives? What are the advantages of adopting this setting over others in this case? How will this affect the results? More details should be furnished.
9. p.12 - specific parameter setting are adopted for BSS algorithm. What are the other feasible alternatives? What are the advantages of adopting this setting over others in this case? How will this affect the results? More details should be furnished.
10. p.13 - several algorithms as shown in Table 1 are adopted as benchmarks for comparison. What are the other feasible alternatives? What are the advantages of adopting these algorithms over others in this case? How will this affect the results? More details should be furnished.
11. The discussion section in the present form is relatively weak and should be strengthened with more details and justifications.
12. Some key parameters are not mentioned. The rationale on the choice of the particular set of parameters should be explained with more details. Have the authors experimented with other sets of values? What are the sensitivities of these parameters on the results?
13. Some assumptions are stated in various sections. More justifications should be provided on these assumptions. Evaluation on how they will affect the results should be made.
14. Moreover, the manuscript could be substantially improved by relying and citing more on recent literature about real-life applications of soft computing techniques in different fields such as the following. Discussions about result comparison and/or incorporation of those concepts in your works are encouraged:
● Devi, RM., et al., “IRKO: An Improved Runge-Kutta Optimization Algorithm for Global Optimization Problems,” Computers,Materials & Continua 70 (3): 4803-4827 2022.
● Gupta, D., et al., “A partition cum unification based genetic-firefly algorithm for single objective optimization,” Sādhanā 46 (3): 121 2021.
● ., et al., “Circulatory System Based Optimization (CSBO): an expert multilevel biologically inspired meta-heuristic algorithm,” Engineering Applications of Computational Fluid Mechanics 16 (1): 1483-1525 2022.
15. Some inconsistencies and minor errors that needed attention are:
● Replace “…based on balanced searching strategy is enlighten by…” with “…based on balanced searching strategy, which is enlightened by…” in line 9 of p.1
● Replace “…combine motion searching with population evolution…” with “…motion searching is combined with population evolution…” in line 13 of p.1
● Replace “…Where, E stands for…” with “…where E stands for…” in line 82 of p.3
● Replace “…Combined with the Figure 4…” with “…Combined with Figure 4…” in line 234 of p.8
● And more…
16. In the conclusion section, the limitations of this study and suggested improvements of this work should be highlighted.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
In this manuscript, the authors propose an evolutionary search algorithm for multi-objective optimization. Generally, the quality of the manuscript is not sufficient for the paper to be published in a high quality scientific journal.
My remarks are as follows:
1. In the abstract and introduction section, rewrite the contributions and highlight the novelty of your research. The terms “information field” and “implicit/explicit information field’ should be defined.
2. At the end of the Introduction section, the description of manuscript structure should be added.
3. The literature review is missing.
4. The authors describe the well-known evolutionary search approach for multi-objective optimization problems (the so-called Best search Strategy – BSS algorithm). There is no novelty in the idea for combination of exploration and exploitation search phases.
5. The experimental settings (“5. Experiment” section”) are not well presented. Please, describe what is given and what should be found in the section.
6. The comparison with results obtained with two existing algorithms (gradient descent algorithm and timing evolution searching) should be analyzed and discussed properly.
7. What are the advantages and disadvantages of the proposed approach in comparison with those of similar previous studies?
The whole manuscript should be edited, because there are some inconsistent and incomplete phrases.
The manuscript does not meet the requirements for publication in a high quality journal as Electronics. I am sorry to reject the manuscript.
The whole manuscript should be edited, because there are some inconsistent and incomplete phrases.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The paper can be accepted.
Author Response
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Author Response File: 
Author Response.docx
Reviewer 2 Report
The most significant comments in the last review (including novelty, major difficulties and challenges, their original achievements to overcome them, etc.) have not been demonstrated satisfactorily. Appropriate revisions to all points raised in the last review should be undertaken in order to justify recommendation for publication.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
The quality of electronics-2440106-peer-review-v2 “A source seeking method for the implicit information field based on a balanced searching strategy” has been improved.
My remark is as follows:
The authors' definition of the term "implicit information field(s)" is generally accurate. However, when it comes to optimal search within an implicit field, such as a magnetic, odor or gravity field, decision makers still require data measurements similar to those needed for explicit data. In this regard, if both cases require the same input data, what is the novelty of the authors' idea?
My recommendation is “Minor revision is needed”.
Moderate editing of the English language is needed.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Round 3
Reviewer 2 Report
The most significant comments in the last review (including novelty, major difficulties and challenges, their original achievements to overcome them, etc.) have not been demonstrated satisfactorily. Appropriate revisions to all points raised in the last review should be undertaken in order to justify recommendation for publication.
