Open Access
E3S Web Conf.
Volume 236, 2021
3rd International Conference on Energy Resources and Sustainable Development (ICERSD 2020)
Article Number 03018
Number of page(s) 4
Section Sustainable Development and Prevention of Urban Environmental Pollution
Published online 09 February 2021
  1. Xia Qin. Total control of water pollutants in the basin. China Environmental Science Press, Beijing,1996. [Google Scholar]
  2. Bai Ximeng, Man Chunsheng. Fuzzy graph tree clustering method in the evaluation of environmental quality. China Environmental Science, 1985,5(6):38~42. [Google Scholar]
  3. Chen Shouyi, Xiong Deqi. Fuzzy set theory and model of lake eutrophication. Journal of Lake Sciences, 1993,5(2):144~152. [Google Scholar]
  4. PAN Z W, JIN J L, WU K Y, et al. Research on the indexes and decision method of regional water environmental system vulnerability. Resources and Environment in theYangtze Basin, 2014, 23(4): 510–530. [Google Scholar]
  5. Li Ruzhong. Progress and trend analysis of theoretical models of water quality assessment. Journal of Hefei University of Technology, 2005,28(4):369~373(inChinese) [Google Scholar]
  6. CARDWELL H, ELLS H. Stochastic dynamic programming models for water quality management[J]. Water Resources Research, 1993,29(4):803–813. [Google Scholar]
  7. Chen Dongjing,Ma Anqing,Xu Dongmin. Factor analysis in water quality assessment. Hydrological,2002,22 (3):29~31. [Google Scholar]
  8. Wang Xiaopeng. The application of multivariate statistical analysis in the evaluation of river pollution. Systems Engineering Theory and Practice, 2001, 21(9):118~123(inChinese) [Google Scholar]
  9. MICHAEL H. On the implementation of fuzzy arithmetical operations for engineering problems[A]. Proceedings of 18th International Conference of the North American Fuzzy Information Processing Society—NAFIPS’99, New York, USA, 1999:462–466. [Google Scholar]
  10. KENTEL E, AREL M M. 2D Monte Carlo versus 2D Fuzzy Monte Carlo health risk assessment[J]. Stochastic Environmental Research and Risk Assessment, 2005,19(1):86–96. [Google Scholar]
  11. GANOULIS J, ANAGNOSTOPOULOS P and MBIMBAS I. Fuzzylogic-based risk analysis of water pollution[A]. Proceedings of 29th Congress of the International Association of Hydraulic Engineering and Research, September 16-21, Beijing, 2001. [Google Scholar]
  12. SILVERT W. Ecological impact classification with fuzzy sets[J]. Ecological Modelling, 1997,96(1-3):1–10. [Google Scholar]
  13. RONALD E G, ROBERT E Y. Analysis of the error in the standard approximation used for multiplication of triangular and trapezoidal fuzzy numbers and the development of a new approximation [J]. Fuzzy Sets and Systems, 1997, 91(1):1–13. [Google Scholar]
  14. RONALD E G, ROBERT E Y. A parametric representation of fuzzy numbers and their arithmetic operators[J]. Fuzzy Sets and Systems, 1997,91(2):185–202. [Google Scholar]
  15. CHEN Shan-huo. Operations of fuzzy numbers with step form membership function using function principle[J]. Information Sciences,1998,108(1-4):149–155. [Google Scholar]
  16. MEHRAN H. Bridging the gap between probabilistic and fuzzy-parameter EOQ[J]. International Journal of Production Economics, 2004, 91(2):215–221. [Google Scholar]

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