PONE-D-23-00226Exploration of the Intelligent-auxiliary Design of Architectural Space Using Artificial Intelligence ModelPLOS ONE

Dear Dr. Li,

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Praveen Kumar Donta, Ph.D.

Academic Editor

PLOS ONE

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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: Partly

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

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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: No

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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: 1.Abstract should reflect the background knowledge on the problem addressed and is need to be added.

2.In Introduction section, the drawbacks of each conventional technique should be described clearly.

3.Introduction section can be extended to add the issues with respect to existing work.

4.Properly define the motivation behind the work.

5.Abstract and Conclusion should be concise yet. But should give complete overview of the work and study.

6.The authors seem to disregard or neglect some important finding in results that have been achieved in paper. So, elaborate and explain the results in more details.

7.Improve the results and discussion section in paragraph.

8.As a conclusion, the technical content is good. Therefore, the contribution of this article is also satisfactory. I am accepting article with minor evision for publication in this journal.

Reviewer #2: This paper discusses the use of deep learning and AI technology to improve the efficiency and reduce the cost of architectural space design. The research also focuses on using semantic networks to explore more scientific and reasonable methods for designing architectural space and on intelligent auxiliary design of architectural space through deep learning in AI. 3D models are chosen as a research object. The research process involves analyzing the overall function, structure and processing of data in architectural space design. I have some remarks below:

The authors use solely pictures to present the process of analyzing the problem. This makes the work unclear.

Article also should explain what exactly are the mentioned nodes and how the scores are evaluated. Preferably using appropriate mathematical notation. I think in this context, the "nodes" refer to the individual units of a neural network, but are those neurons or layers or networks? Who knows?

It is unclear if the space temperature and humidity refer to the actual ambient parameters of architectonic space or are they some complexity coefficients for deep learning process characteristics. It seems to me that in the context of article, the "temperature and humidity" likely refers to the internal temperature and humidity levels of the architectural space being studied. How the scores of these two are defined? The authors might have used a subjective or objective method like a survey, sensor data, or a specific formula to generate the scores, but the text doesn't provide enough information to know for sure.

This sentence is unclear:

“As the number of network nodes increases, the model fitting degree of different architectural space auxiliary models and the conformity of the predicted value of the architectural space auxiliary models are shown in Fig. 7 and Fig. 8, respectively.”

There are several numerical results presented. These values include the architectural design error, accuracy loss, model fitting degree, conformity of predicted value, space temperature score, and space humidity score. How were they calculated? It's likely that these values are calculated based on some form of measurement or data collection, but the article does not give details about the specific methods used to generate them. Pictures do little to explain it.

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Reviewer #1: No

Reviewer #2: No

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Exploration of the Intelligent-auxiliary Design of Architectural Space Using Artificial Intelligence Model

PONE-D-23-00226R1

Dear Dr. Li,

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,

Praveen Kumar Donta, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

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 #1: All comments have been addressed

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 #1: Yes

Reviewer #2: (No Response)

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

Reviewer #1: Yes

Reviewer #2: (No Response)

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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 #1: Yes

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 #1: Yes

Reviewer #2: (No Response)

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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 #1: All the comments raised are addressed well by the reviewers.

The paper is accepted in present form for publication.

Reviewer #2: (No Response)

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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 #1: No

Reviewer #2: No

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