PONE-D-25-29709Forecasting China's shipping indices based on modal decomposition and optimized deep learning integrated modelPLOS ONE

Dear Dr. ZOU,

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Qichun Zhang, PhD

Academic Editor

PLOS ONE

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Additional Editor Comments:

A number of the comments have been received for this submission. More details are needed to address all these comments. Thus a major revision is essential for this paper.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Below are my suggestions for improvement.

About Manuscript Structure

1. Inclusion of a Dedicated Introduction Section: The manuscript currently moves directly from the Abstract to the Materials and Methods. I strongly recommend adding a distinct "Introduction" section.

2. Logical Ordering of Methodological Concepts: Your workflow is presented as VMD -> CPSO -> BiLSTM, but the introduction of these concepts in the introductory parts of the paper does not follow this logical order, with VMD being mentioned last. To improve clarity, I suggest reorganizing the introduction of these methods to mirror the order in which they are actually applied in your research. This will allow readers to follow your methodological approach more intuitively.

3. Placement of "Related Work" Comparison: You provide a comparison with a similarly structured model, CEEMD-PSO-BiLSTM, in the Conclusion and Discussion section. I would advise moving this discussion to the new "Introduction" section, or potentially creating a "Related Work" section. Placing this comparison earlier in the manuscript will help to highlight the novelty and contribution of your proposed model right from the start.

About Presentation

1. Standardize Abbreviations: On first use, define all abbreviations using the format "Full Name (Abbreviation)". Use only the abbreviation thereafter. A thorough check of the entire paper is required.

2. Illustrate the VMD Process: Add a flowchart or a formal algorithm to clearly illustrate its procedural steps.

3. Define Equation Notations: Immediately following every equation, you must explicitly define all mathematical notations used. Apply this consistently across the entire paper.

4. Unify Index Order: The presentation order of your four indices is inconsistent. In lines 304-314, you discuss CDBI before SCFI, which contradicts the CCFI, SCFI, CDBI, CBFI order used elsewhere. Please correct this for consistency.

5. Clarify Figure and Table Elements: Before analyzing any data in figures or tables, define all non-standard terms, abbreviations, and units within the caption or main text (e.g., explain ADF and the meaning of the p-value before discussing Table 1).

6. Unify Data Formatting: Ensure consistent data formatting within and across tables. For example, the decimal places for corresponding items in Table 5 and Table 6 should be uniform.

7. Correct Cross-References: Check the entire manuscript to ensure all your cross-references are in the right format.

About Experiments and Results Analysis

1. Inconsistent Units in Table 2: The unit for CDBI in Table 2 differs from other indices. Justify this discrepancy.

2. Justify Multi-Step Prediction: The comparison between 1-step and multi-step predictions currently rests only on accuracy. What is the motivation for including multi-step analysis? If it offers other advantages (e.g., efficiency, generality), analyze them. Otherwise, its purpose is unclear.

3. Explain Anomalous Results in Table 6: In your multi-step predictions (Table 6), the CPSO-BiLSTM model yields higher errors for the CDBI index than the standard PSO-BiLSTM. Explain this result.

4. Redundant Comparison and Potential Error: You have already established that CPSO-BiLSTM outperforms PSO-BiLSTM. Therefore, the comparison between VMD-CPSO-BiLSTM and VMD-PSO-BiLSTM seems redundant. What is the scientific justification for this experiment? Furthermore, lines 513-514 claim VMD-PSO-BiLSTM is superior to VMD-CPSO-BiLSTM, which directly contradicts your other findings. Is this a clerical error? Clarify the logic and correct any mistakes.

5. Add Essential Comparative Experiment: Your paper discusses the CEEMD-PSO-BiLSTM model. A direct experimental comparison with your proposed model is essential to validate your claims of superiority. This experiment should be conducted and included.

Reviewer #2: The abstract clearly presents a hybrid forecasting model, VMD-CPSO-BiLSTM, designed specifically for predicting China's shipping indices.

1. What is the difference between CPSO and PSO?

2. Need to add Justification for CPSO over PSO.

3. How long VMD, CPSO, BiLSTM takes (Time)

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Reviewer #1: No

Reviewer #2: No

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Forecasting China's shipping indices based on modal decomposition and optimized deep learning integrated model

PONE-D-25-29709R1

Dear Dr. ZOU,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Qichun Zhang, PhD

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: (No Response)

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Thanks for the authors for addressed all comments and rewrite a good paper with good idea.

I recommended to accept this work.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

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