Applied and Computational Mathematics

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Urban Smart Growth Mathematical Model and Application

Received: Jun. 25, 2018    Accepted:     Published: Jun. 26, 2018
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Abstract

In view of urban sprawl brought about by urbanization development, this paper establishes a weighted comprehensive evaluation model to measure the city’s smart growth status. Bordeaux is selected as the research object, and relevant data are collected and processed. The data is then substituted into the established model to solve the problem. The results show that some indicators in the city are still at a poor level. Combining the indicators with higher weights and lower scores in the evaluation results, a better urban smart growth plan was proposed. Finally, the ARIMA forecasting model is used to predict the indicators in the future more than ten years. The results verify the effectiveness of the urban smart growth plan and the potential of the plans.

DOI 10.11648/j.acm.20180703.12
Published in Applied and Computational Mathematics ( Volume 7, Issue 3, June 2018 )
Page(s) 83-88
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Urban Smart Growth, Weighted Comprehensive Evaluation, ARIMA Forecast

References
[1] Cheng Maoji. Research on Nanjing City Growth Evaluation and Optimization Based on Smart Growth [D]. Nanjing Normal University, 2012.
[2] Ruan Zhanfu. Research on Urban Spatial Expansion Based on Smart Growth [D]. Northwest Normal University, 2009.
[3] Guan Jing. A Review of Research on Smart Growth [J]. Research on Financial and Economic Issues, 2013 (02): 26-31.
[4] Ruan Zhanfu. Research on Urban Spatial Expansion Based on Smart Growth [D]. Northwest Normal University, 2009.
[5] Zhou Rong, Wang Qian, Wang Yanhui. Mathematical model of "smart growth" in cities [J]. Mathematic Modeling and Applications, 2017, 6 (02): 16-24.
[6] Li Qin. Evaluation of Urban Smart Growth Based on Principal Component Analysis [J]. Urban Construction Theory Research, 2016 (23): 11.
[7] Liu Yan, Zhu Jiaming. Evaluation and Grey Prediction of Urban Smart Growth Based on Fuzzy Comprehensive Method [J]. Journal of Chifeng College (Natural Science Edition), 2017, 33 (15): 29-32.
[8] Wang Bangli, Huang Wenquan, Li Kaishi. Research on Product Material Selection Based on Analytic Hierarchy Process and Weighted Evaluation Method [J]. Journal of Sichuan University of Science & Engineering (Natural Science Edition), 2013, 26 (05): 71-73.
[9] Sun Huichao, Cheng Gang, Li Yuli, Huang Ningning. Study on Comprehensive Evaluation System of Urbanization Development Level [J]. Journal of Henan University of Urban Construction, 2016, 25 (05): 53-60+87.
[10] Li Hailin. Research on feature representation and similarity measurement methods in time series data mining [D]. Dalian University of Technology, 2012.
[11] Yuan Jidong, Wang Zhihai. A Summary of Time Series Representation and Classification Algorithms [J]. Computer Science, 2015, 42 (03): 1-7.
Cite This Article
  • APA Style

    Geng Liu, Xiao Han, Zhen Li. (2018). Urban Smart Growth Mathematical Model and Application. Applied and Computational Mathematics, 7(3), 83-88. https://doi.org/10.11648/j.acm.20180703.12

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    ACS Style

    Geng Liu; Xiao Han; Zhen Li. Urban Smart Growth Mathematical Model and Application. Appl. Comput. Math. 2018, 7(3), 83-88. doi: 10.11648/j.acm.20180703.12

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    AMA Style

    Geng Liu, Xiao Han, Zhen Li. Urban Smart Growth Mathematical Model and Application. Appl Comput Math. 2018;7(3):83-88. doi: 10.11648/j.acm.20180703.12

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  • @article{10.11648/j.acm.20180703.12,
      author = {Geng Liu and Xiao Han and Zhen Li},
      title = {Urban Smart Growth Mathematical Model and Application},
      journal = {Applied and Computational Mathematics},
      volume = {7},
      number = {3},
      pages = {83-88},
      doi = {10.11648/j.acm.20180703.12},
      url = {https://doi.org/10.11648/j.acm.20180703.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.acm.20180703.12},
      abstract = {In view of urban sprawl brought about by urbanization development, this paper establishes a weighted comprehensive evaluation model to measure the city’s smart growth status. Bordeaux is selected as the research object, and relevant data are collected and processed. The data is then substituted into the established model to solve the problem. The results show that some indicators in the city are still at a poor level. Combining the indicators with higher weights and lower scores in the evaluation results, a better urban smart growth plan was proposed. Finally, the ARIMA forecasting model is used to predict the indicators in the future more than ten years. The results verify the effectiveness of the urban smart growth plan and the potential of the plans.},
     year = {2018}
    }
    

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    T1  - Urban Smart Growth Mathematical Model and Application
    AU  - Geng Liu
    AU  - Xiao Han
    AU  - Zhen Li
    Y1  - 2018/06/26
    PY  - 2018
    N1  - https://doi.org/10.11648/j.acm.20180703.12
    DO  - 10.11648/j.acm.20180703.12
    T2  - Applied and Computational Mathematics
    JF  - Applied and Computational Mathematics
    JO  - Applied and Computational Mathematics
    SP  - 83
    EP  - 88
    PB  - Science Publishing Group
    SN  - 2328-5613
    UR  - https://doi.org/10.11648/j.acm.20180703.12
    AB  - In view of urban sprawl brought about by urbanization development, this paper establishes a weighted comprehensive evaluation model to measure the city’s smart growth status. Bordeaux is selected as the research object, and relevant data are collected and processed. The data is then substituted into the established model to solve the problem. The results show that some indicators in the city are still at a poor level. Combining the indicators with higher weights and lower scores in the evaluation results, a better urban smart growth plan was proposed. Finally, the ARIMA forecasting model is used to predict the indicators in the future more than ten years. The results verify the effectiveness of the urban smart growth plan and the potential of the plans.
    VL  - 7
    IS  - 3
    ER  - 

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Author Information
  • Basic Teaching Department, Rongcheng College of Harbin University of Science and Technology, Weihai, P. R. China

  • Electrical Engineering Department, Rongcheng College of Harbin University of Science and Technology, Weihai, P. R. China

  • Mechanical Engineering Department, Rongcheng College of Harbin University of Science and Technology, Weihai, P. R. China

  • Section