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Cluster Computing

, Volume 22, Supplement 3, pp 6335–6343 | Cite as

Study on coordinated development of urban environment and economy based on cluster computing

  • Pengyu ChenEmail author
Article

Abstract

In the continuously developing economic society, improving the environmental situation is a difficult task with fast economic growth. Therefore, it is significant to study the coordinated development of urban environment and economy. We made an empirical analysis on Environmental Kuznets Curve (EKC) of the relationship between economic growth and environmental pollution in Jiangsu Province by cluster computing based on cluster server database. With EKC model, the relationship between environmental pollution and economic growth and its development in Jiangsu Province was studied to conclude the internal relation between ecological environment and economic growth. The work provides theoretical guidance to government decision-making and industrial revolution.

Keywords

Cluster computing Coordinated development EKC Environment and economy 

References

  1. 1.
    Grossman, G.M., Krueger, A.B.: Economics growth and the environment. Q. J. Econ. 110(2), 353–377 (1995)CrossRefGoogle Scholar
  2. 2.
    Panayotou, T.: Empirical Tests and Policy Analysis of Environmental Degradation at Different Stages of Economic Development ILO. Technology and Employment Programmer, Geneva (1999)Google Scholar
  3. 3.
    Meyer, B., Distelkamp, M., Wolter, M.I.: Material efficiency and economic-environmental sustainability: results of simulations for germany with the model Panta Rhei. Ecol. Econ. 63, 192–200 (2007)CrossRefGoogle Scholar
  4. 4.
    Dasgupta, S., Mody, A., Roy, S., Wheeler, D.: Environmental regulation and development: across-country empirical analysis. Oxf. Dev. Stud. 29(2), 173–187 (2001)CrossRefGoogle Scholar
  5. 5.
    Penn, A.S., Knight, C.J.: Extending participatory fuzzy cognitive mapping with a control nodes methodology: a case study of the development of a bio-based economy in the humber region, UK. In: Environmental Modeling with Stakeholders, pp. 171–188 (2017)Google Scholar
  6. 6.
    World Bank: Monitoring Environment Progress. The World Bank Press, Washington D.C., pp. 5–116 (1995)Google Scholar
  7. 7.
    Zheng, H., Wang, Y.: A research review on green development indicator system. J. Ind. Technol. Econ. 2, 142–152 (2013)Google Scholar
  8. 8.
    Pulselli, F.M., Luca, C., Bastianoni, S.: Ecosystem services as acounter-part of energy flows to ecosystems. Ecol. Model. 222, 2924–2928 (2011)CrossRefGoogle Scholar
  9. 9.
    Ma, Y., Yang, S.: Study on the evaluation of environmental and economic coordination in Shihezi city. J. Heilongjiang Vocat. Inst. Ecol. Eng. 21(5), 5–7 (2008)Google Scholar
  10. 10.
    Li, S., Liu, Y.: An analysis from economics on the harmonious develo pment of economy and environment. J. Beijing Polytech. Univ. 1(3), 1–6 (2001)Google Scholar
  11. 11.
    Wang, J., Tang, X.: Regional comparisons of environment-economy coordinated development within Fujian Province. J. Subtrop. Resour. Environment 6(3), 48–54 (2011)Google Scholar
  12. 12.
    Wang, Y., Li, J.: Coupling coordination evaluation method between eco-environment quality and economic development level in contiguous special poverty-stricken areas of China. Chin. J. Appl. Ecol. 26(5), 1519–1530 (2015)MathSciNetGoogle Scholar
  13. 13.
    Zhang, R., Jiao, H.: Coupling and coordinating between economic development and ecological environment in the Pan Yangtze River delta. Resour Environ. Yangtze Basin 5(24), 719–727 (2015)Google Scholar
  14. 14.
    Zhou, Q., Luo, J.: The risk management using limit theory of statistics on extremes on the big data era. J. Comput. Theor. Nanosci. 12, 6237–6243 (2015).  https://doi.org/10.1166/jctn.2015.4661 CrossRefGoogle Scholar
  15. 15.
    Zhou, Q.: Cluster Comput. 19, 1275 (2016).  https://doi.org/10.1007/s10586-016-0580-y CrossRefGoogle Scholar
  16. 16.
    Zhou, Q., Luo, J.: The study on evaluation method of urban network security in the big data era. Intell. Autom. Soft Comput. (2017).  https://doi.org/10.1080/10798587.2016.1267444 CrossRefGoogle Scholar
  17. 17.
    Zhou, Q.: Electron. Commer. Res. (2017).  https://doi.org/10.1007/s10660-017-9265-8 CrossRefGoogle Scholar
  18. 18.
    Xie, J., Luo, J., Zhou, Q.: Clust. Comput. 19, 1885 (2016).  https://doi.org/10.1007/s10586-016-0657-7 CrossRefGoogle Scholar
  19. 19.
    Hennicker, R., Bauer, S.S., Janisch, S., Ludwig, M.: A generic framework for multi-disciplinary environmental modeling. Model. Softw. Soc. 980–994 (2010)Google Scholar
  20. 20.
    Videira, N., Antunes, P., Santos, R.: Engaging stakeholders in environmental and sustainability decisions with participatory system dynamics modeling. In: Gray, S., et al. (eds.) Environmental Modeling with Stakeholders, pp. 241–265. Springer, Cham (2017)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Economics & ManagementNorthwest UniversityXi’anChina

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