Least Squares in a Data Fusion Scenario via Aggregation Operators
Round 1
Reviewer 1 Report
Abstract:
1.1 There are parts were repeated in the conclusion! Try to use different expressions.
1.2. The authors stated that "Numerical examples about fitting….." only one example can be found? The authors should provide more numerical examples.
1.3 The advantages and disadvantages of the applied method should be included.
2. Introduction:
2.1 This section is not acceptable; Literary survey is very poor.
2.2 Include the novelty of the presented study.
3. Analyses:
3.1 There are various Aggregation Operators such as AM, WM, OWA, WOWA,…. Why the authors choose OWA operator, Choquet integral operator, and mixture operator?
3.2 Is there any additional conditions can be found on the used weight functions?
3.3 Revise the proof of the theorem 3.1.
4. Conclusions:
4.1 This part is very poor, include the major outcomes of you study.
5. Update your references list.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The paper needs significant improvements, please, find the pdf file.
Comments for author File: Comments.pdf
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
The manuscript proposed a Least Squares Aggregation Operators to fuse data. The manuscript can be accepted in presented form but before accepting it, authors have to show some sample calculation in manuscript with regard to generate equations (68, 69, 70) in order to lucid understand of this manuscript.
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
Authors propose an introductory application of Least Square Methods (LSM) to the analysis of information from different sources. As stated by the document, the number of real world problems involving the management of different and heterogeneous data sources is increasing and getting a large amount of attention. In this sense, the proposal is interesting and promising. But, in my humble opinion, the paper needs a deeper justification and discussion of the stated problem.
Authors develop a methodology for LSM application on scenarios needing aggregation measures. In particular, they extend well known techniques as OWA operators, Choquet integral and mixture operator to be applied on data coming from several sources. Abstract seems too short, and the problem should be stated and introduced in more detail.
The technical proposal of the measures is well described and detailed but, again, the numerical example seems too simple and ill-described. How are these data sets generated? What they can represent? How different are they in order to properly establish a good method for information fusion? The results are presented in an obscure way. It should be better and easier to understand by the reader to present the results by means of tables, where the authors could remark the more relevant values obtained. A better and extended discussion about the results should be needed.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
There are some minor language issues througout the paper.
Author Response
Dear reviewer,
One again, we would like to express our sincere appreciation of the kindly observations in order to improve the quality of the paper. We have made all corrections suggested by the reviewer and we hope that now the paper has the quality necessary for publishing in this renewed journal. The improvements are commented below.
Author Response File: Author Response.pdf
Reviewer 2 Report
Technical comments and some possible directions for improvements:
1. page 2, 1 ≤ i ≤ k should be 1≤ i< k (see, example 1 on page 36 in [22])
2. Please, don’t use this strange notation, what this represents Jk(x)Wk=? (22)-(23)
3. Please, don’t use this notation, what this represents Ì…Jk(x)Iμ(Gk) ? line 187 - line 189
4. Please, don’t use this notation, what this represents Jk(x)Wk ? (60)-(61)
5. superfluous \sum_{i=1}^L in (43) and above
6. after replacing, missing \sum_{i=1}^L (38), (46), (53)
7. Correct line 201, In future studies, For future work
Author Response
Dear reviewer,
One again, we would like to express our sincere appreciation of the kindly observations in order to improve the quality of the paper. We have made all corrections suggested by the reviewer and we hope that now the paper has the quality necessary for publishing in this renewed journal. The improvements are commented below.
Author Response File: Author Response.pdf
Reviewer 4 Report
Authors propose an extension of Least Square Method (LSM) based on some well-known aggregation methods, as a way to apply it on problems that need to integrate data coming from different sources.
The proposal is interesting and the methods are properly presented and described. It must be acknowledged to the authors the effort made in the improvement of the original manuscript.
Still, the initial results shown by the experiments could be emphasized in a larger way, for example, by means of a table that summarize the obtained indexes, allowing to compare them in an easier way.
There are some minor language issues througout the paper.
In page 1, line 17, there seems to be an empty reference: "in a scenario where data comes from different sources []".
In page 15, line 270, the sentence "The Tables (2) and (3) to shows sample with regard to x1 and x2, respectively" seems malformed.
In page 15, line 291, the sentence "In future studies, For future work, we want to explore..." shows a redundant form.
Author Response
Dear reviewer,
One again, we would like to express our sincere appreciation of the kindly observations in order to improve the quality of the paper. We have made all corrections suggested by the reviewer and we hope that now the paper has the quality necessary for publishing in this renewed journal. The improvements are commented below.
Author Response File: Author Response.pdf
