Open Access
Issue
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
DOI https://doi.org/10.1051/e3sconf/202123603018
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]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.