n-Dimensional Chaotic Time Series Prediction Method

Round 1

Reviewer 1 Report

This article needs to address following comments:

1. I am surprised to see casual approach of authors by putting following details of template:

"The Materials and Methods should be described with sufficient details to allow others to replicate and build on the published results. Please note that the publication of your 95 manuscript implicates that you must make all materials, data, computer code, and proto- 96 cols associated with the publication available to readers. Please disclose at the submission 97 stage any restrictions on the availability of materials or information. New methods and 98 protocols should be described in detail while well-established methods can be briefly de- 99 scribed and appropriately cited."

2.  You must add details after main heading of section 2. Do not jump directly with Figure there.

3.  Call out all the equations in the text. Few are missing like equation 2. 

4.  Findings in Fig. 3 and 4 are not clear. Drawn with poor resolution.

5.  Be consistent in using terms- "Logistic chaotic time series ". Either put all with first capital letter or everything in lower alphabets.

6.  I suggest authors to cover the angle of computational efficiency of model as well. It is important to analyze computational efficiency of chaotic time series predictions especially with n dimensions.

7. I suggest you to provide comparison of your model with existing works in tabular form and write by which factor your model outperforms them.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

MERITS

- the approached subject is highly actual, with direct applications in wave and wind energy

- the proposed method provides considerably lower errors comparing with classical methods

- accurate presentation of the tests' results

CRITIQUE

- there are some editing errors

- there is no indication regarding the implementation of the proposed algorithm, software support etc.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Introduction- correct

lines 94-99 should be removed.

The article is well written, the experiment is ok. However, the authors should describe the dataset they used. Could this experiment be replicated on another dataset? Explain.

Besides that, a very good job.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Most of the comments are addressed in the revised version. However, comment 7 is still not addressed. 

"I suggest you to provide comparison of your model with existing works in tabular form and write by which factor your model outperforms them"

Table 4 is not addressing my comment. Relate your work with state-of-the-art and show how your work outperforms. 

You went for lot of critics in the introduction for existing works. You need to prove that how you outperformed them here by giving comparison. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf