Analyzing the Passenger Flow of Urban Rail Transit Stations by Using Entropy Weight-Grey Correlation Model: A Case Study of Shanghai in China

Round 1

Reviewer 1 Report

The article is devoted to a topical applied problem of the analysis of traffic flows in the world's largest metropolis of Shanghai. The title of the article does not match its content. The article doesn’t offer any mathematical model. Instead, it provides a diagram of the transport network, the location of transport hubs, universities, shopping centers and other factors that can affect traffic flows. The analysis of correlations of traffic flows and normalized estimates of factors is carried out, for which the authors choose the simplest methods of factor analysis, such as the calculation of average values, variances, correlations. The content of the article hardly corresponds to the profile of the journal "Mathematics".

Author Response

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Reviewer 2 Report

The article is written on a topical issue related to the optimization of the passenger flow of transit railway stations. Classical modeling tool is used as mathematical models

analysis - a mathematical model of the entropy correlation of weight, which in itself is not original and new. Nevertheless, the conclusions and recommendations for optimizing the passenger flow of transit railway stations are of practical interest and are confirmed mathematically, which can serve as a significant result. There are several recommendations that would help improve this work:

- It would be nice to consider other modeling methods, for example, dynamic modeling, system dynamics, discrete-event and agent-based modeling, etc., and justify the advantages of the considered method.

- Is it possible to conduct a full-scale experiment of approbation of the proposed model? If this is possible, then the article should write about it.

Author Response

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Reviewer 3 Report

The paper proposes a mathematical model for the correlation of the entropy of weight and gray color for the analysis of passenger traffic in the city railway station in order to optimize it and ensure the effective development of railway transport. On the basis of a mathematical model of entropy weight correlation, the factors that affect the passenger traffic of railway transit stations are studied using the example of Shanghai. As a result of the study, it was found that the number of the population of the area, the distance from the railway interchange station to public facilities, the cost of the trip and services, etc., which are studied in detail in the work, have a significant impact on passenger traffic.

The relevance of the study lies in the fact that the proposed solutions for optimizing the railway transport system will save energy, reduce noise and carbon dioxide emissions and reduce congestion in cities. And this, in turn, contributes to the sustainable development of large cities, public transport systems. The results obtained can be used by local authorities to optimally plan the choice of site and location of the station, optimize metro lines and adopt effective policies for the sustainable development of city railway station.

In the proposed article, to eliminate the shortcomings of regression models for studying passenger traffic, a gray relational method is proposed to analyze the factors affecting the passenger traffic of railway transport, and entropy is taken into account when calculating the weight to improve the accuracy of the calculation. According to the results of the degree of gray correlation, it is shown that transport accessibility, built-up environment, regional features of the area to which the railway leads, station conditions and spatial location significantly affect the passenger flow of the station. The presented work, based on a combination of Gray's relational method and entropy theory, presents a mathematical model for the analysis of factors that affect the passenger flow of city rail transport and transit stations.

 In section 5 - Results and Discussion, the influence of 5 main factors on the passenger traffic of railway stations is examined in detail. Based on the developed model and collected data, a gray correlation between passenger traffic and 5 main factors affecting passenger traffic were determined. Based on the calculated values of entropy weights (between 0.025 and 0.3), it is found that the data of the entire system is relatively ordered, and the analysis of the results based on the collected data is more scientific and rigorous.

In general, the work is useful and practical, since the results of the study can be used to make a scientifically based decision by local authorities in large cities to ensure the efficient and sustainable development of railway transport. The work as a whole is evaluated positively, and it can be recommended for publication.

At the same time, some remarks can be singled out, the elimination of which can improve the content and structure of the work.

1.       In section 1-Introduction, it should be noted about the approaches to building the developed models in the conditions of fuzziness of some important part of the initial information, referring, for example, to the work published in the journal Energies DOI 10.3390/en15041573

https://www.scopus.com/record/display.uri?eid=2-s2.0-85125200455&origin=resultslist&sort=plf-f&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1,FEATURE_EXPORT_REDESIGN:1  and  Bulletin of the Tomsk Polytechnic University, Geo Assets Eng. DOI 10.18799/24131830/2019/7/2194

https://www.scopus.com/record/display.uri?eid=2-s2.0-85074746106&origin=resultslist&sort=plf-f&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1,FEATURE_EXPORT_REDESIGN:1 and etc.

2.       It was necessary to explain the meaning of the numerical designation in sections, for example: ... and policies 1; …the station 2; … subways 4 and others, otherwise they raise certain questions.

3. The work used data from 2015, it would be desirable to use at least averaged data for the last 3-5 years (this is a wish, maybe for the future).

4. In section 6-Conclusions and suggestions, it is desirable to highlight the novelties of our own results.

Authors are encouraged to address the above comments and consider recommendations before making a final decision by the editor.

Author Response

Please see the attachment. Thank you.

Author Response File: Author Response.doc

Round 2

Reviewer 1 Report

The content of the article hardly corresponds to the profile of the journal "Mathematics".

Author Response

Please see the attachment. Thank you.

Author Response File: Author Response.doc