Training forecast to football athletes using Hopfield neural networks based on Markov matrix

Hongxing Peng; Li Li; Long Cheng

doi:10.1371/journal.pone.0317604

Peer Review History

Original SubmissionJuly 3, 2024
3 Jul 2024 Author Response https://doi.org/10.1371/journal.pone.0317604.r001
25 Sep 2024 Decision Letter - Perepi Rajarajeswari, Editor Dear Dr. peng, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Nov 09 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. 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Please do not edit.] [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0317604.r002
Revision 1
1 Oct 2024 Author Response Dear Editor and Reviewers, Many thanks for your insightful and informative comments which are very helpful for the further improvement of this work. We have revised this manuscript according to the reviewers’ comments and gave the detailed responses to their questions one by one in the following “Response to Reviewers’ comments”. Best regards, Hongxing Peng Comments: 1. Add more new contributions to the manuscript Response: Many thanks for the insight comments. The revision was marked with the red. New contributions are added, and please see Line #78 to Line #81. 2. Apply Evaluation metric and testing strategies to the proposed model Response: We applied two evaluation metrics Precision and F1-score to test the forecast ability of the proposed model, please see Section 5.2 in Line # 295 to Line #304. Additionally, we compared the running efficiency of the proposed model with that of the competitors. Please see Section 5.3 in Line #305 to Line #318. 3. Technically paper is sound. Response: Many thanks for the comments. 4. Use technical writing for improving the quality of manuscript. Response: We revised carefully this paper and made some minor adjustments to highlight the contributions. 5. The manuscript will be accepted after making changes. Response: Many thanks for the comments Attachments Attachment Submitted filename: responseletter-2024-9-30.docx https://doi.org/10.1371/journal.pone.0317604.r003
12 Nov 2024 Decision Letter - Perepi Rajarajeswari, Editor Dear Dr. peng, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Dec 27 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols . We look forward to receiving your revised manuscript. Kind regards, Perepi Rajarajeswari Academic Editor PLOS ONE Additional Editor Comments: Dear sir, Pls do all the comments according to reviewer comments and follow journal guidelines. With regards Dr Perepi Rajarajeswari Academic editor [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author Reviewer #1: (No Response) ******** 2. Is the manuscript technically sound, and do the data support the conclusions??> Reviewer #1: No ****** 3. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: No ****** 4. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: No ****** Reviewer #1: This paper proposes a neural network based on the Markov probability transition matrix to predict the training performance of football athletes. This paper has been revised according to the previous comments. However, the readability and writing are unsatisfactory. Some comments are as follows: 1. The language should be polished. The logic in Section 1 Introduction is confused. 2. The quality of Figure 1 “The structure of DHNNs.” is unsatisfactory. 3. The control scheme seem to be simple validate of the existing predictive algorithm. The highlights of the work is unobvious. 4. The simulation process is too simple. Only bar charts are provided cannot be accepted. ****** 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 #1: Yes: Xin Hu ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0317604.r004
Revision 2
25 Dec 2024 Author Response Dear Editor and Reviewers, Many thanks for your insightful and informative comments. We have revised this manuscript according to the reviewers’ comments and gave the detailed responses to their questions one by one in the following “Response to Reviewers’ comments”. Best regards, Yours sincerely, Hongxing Peng Reviewer #1: This paper proposes a neural network based on the Markov probability transition matrix to predict the training performance of football athletes. This paper has been revised according to the previous comments. However, the readability and writing are unsatisfactory. Some comments are as follows: 1. The language should be polished. The logic in Section 1 Introduction is confused. Many thanks for the insightful comments. The revision was marked with the red. Response: We rewrote the Section 1 Introduction and organized the section to understand the logical. Please see Line #30 to Line #92. 2. The quality of Figure 1 “The structure of DHNNs.” is unsatisfactory. Response: We re-drew the Fig. 1, please see Line #199. 3. The control scheme seem to be simple validate of the existing predictive algorithm. The highlights of the work are unobvious. Response: We supplemented two evaluated metrics Accuracy and G-score, then we compared our model with the four competitors. Additionally, we conducted statistical analysis on these results. Please see Line #326 to Line #340. 4. The simulation process is too simple. Only bar charts are provided cannot be accepted. Response: We supplemented the experiments in Section 5.1. Our goal is to analyze the factors that affect athlete training performance of football athletes, therefore, we used the SPSS tool to analyze the relations between the seven training indicators and the forecast training performance. Please see Line #293 to Line #298. To further observe the seven training indicators, we used k-means clustering to cluster the seven training indicators. Please see Line #308 to Line #314. Meanwhile, we visualized the clustered results in Fig. 3 in Line #319. Additionally, we analyzed the training loss and testing loss of our model in Line #315 to Line #318. And please see the Fig. 4 in Line #324. Attachments Attachment Submitted filename: R2-responseLetter.docx https://doi.org/10.1371/journal.pone.0317604.r005
2 Jan 2025 Decision Letter - Perepi Rajarajeswari, Editor Training forecast to football athletes using Hopfield neural networks based on Markov matrix PONE-D-24-27336R2 Dear Dr. hongxing peng, 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. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. 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, Perepi Rajarajeswari Academic Editor PLOS ONE Additional Editor Comments (optional): Now the paper is in accepted. Reviewers' comments: https://doi.org/10.1371/journal.pone.0317604.r006
Formally Accepted
Acceptance Letter - Perepi Rajarajeswari, Editor PONE-D-24-27336R2 PLOS ONE Dear Dr. peng, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. 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. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Perepi Rajarajeswari Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0317604.r007

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