Transactions of Tianjin University

, Volume 23, Issue 3, pp 267–276 | Cite as

Real-Time Update of Sequence Placement Logic for High Arch Dams Based on Evidence Weight Discount

  • Tao Guan
  • Denghua Zhong
  • Bingyu Ren
Research article


Sequence placement logic plays a significant role in construction simulation of high arch dams and directly affects the simulation process and results. To establish a sequence logic for dam block placement, the construction scheme, real-time construction process, and random factors of the site all need to be considered in detail. There are few studies available currently that take all these factors into consideration. To address this problem, a real-time update of sequence placement logic for high arch dams based on evidence weight discount is proposed in this study. First, the subjective weight of the dam block sequence priority criteria is built using a consistent matrix method based on the construction scheme. Second, using evidence theory, dynamic objective weight of the priority criteria and basic probability assignment is built. Finally, using a weight self-adaptive adjustment method and comprehensive evidence discounting, the placing probabilities of different dam blocks are obtained. A case study indicates that this method can realize real-time update of sequence placement logic.


Sequence placement logic Evidence theory Weight self-adaptive adjustment method Evidence weight discount Real-time update 



This study was supported by the Foundation for Innovative Research Groups of National Natural Science Foundation of China (No. 51321065), the Foundation for Key Program of Natural Science Foundation of High Arch Dam (No. 51339003), and the National Basic Research Program of China (“973” Program, No. 2013CB035904).


  1. 1.
    Denghua Zhong, Jingru Li, Huirong Zhu et al (2004) Geographic information system-based visual simulation methodology and its application in concrete dam construction processes. J Constr Eng Manag 130(5):742–750CrossRefGoogle Scholar
  2. 2.
    Bian X, Hu Z (2014) Sequencing for concrete dam placement based on grey correlation and evidential reasoning. Eng J Wuhan Univ 47(3):294–299 (in Chinese) Google Scholar
  3. 3.
    Qingming Wu, Dong Chen (2000) Simulation on concrete dam placement arrangement. Yangtze River 31(5):41–43 (in Chinese) Google Scholar
  4. 4.
    Xiong H, Yang D, Liu W et al (2010) Dynamic optimization model of concrete dam placement based on entropy weight multi-objective decision-making. Const Hydraul Power 4:12–15 (in Chinese) Google Scholar
  5. 5.
    Zhong D, Wu K, Lian J et al (2008) Research on concreting sequencing for dam construction based on fuzzy rule. J Syst Simul 20(5):1099–1102 (in Chinese) Google Scholar
  6. 6.
    Liu Q (2003) Construction diversion risk analysis and visualization of construction process simulation. Wuhan University, Wuhan (in Chinese) Google Scholar
  7. 7.
    He L, Zhang C, Jiang P (2014) New conflict evidence fusion method based on confidence distance. Appl Res Comput 31(10):3041–3043 (in Chinese) Google Scholar
  8. 8.
    Luo H, Yang SL, Hu XJ et al (2012) Agent oriented intelligent fault diagnosis system using evidence theory. Expert Syst Appl 39(3):2524–2531CrossRefGoogle Scholar
  9. 9.
    Li D, Lian J, Su F et al (2015) An improved method based on D-S evidence theory and its verification in damage location for guide wall structure. Adv Sci Technol Water Resour 35(1):78–84 (in Chinese) Google Scholar
  10. 10.
    Wang J (2013) Evaluation research on the competitiveness of creative industry park based on evidence theory. Inf Technol J 12(15):3249–3252CrossRefGoogle Scholar
  11. 11.
    Fu Y (2010) Researches on uncertain multi-attribute decision-making based on evidential reasoning. Northeastern University, Shenyang (in Chinese) Google Scholar
  12. 12.
    Jin J, Wu Y, Wang M (2004) Combined weight method for optimal selection of city flood control standard schemes. J Sichuan Univ Eng Sci Ed 36(4):1–5 (in Chinese) Google Scholar
  13. 13.
    Ji Liu, Bende Wang (2009) Variable fuzzy model based on combined weights and its application to risk assessment for flood control engineering. J Dalian Univ Technol 49(2):272–275 (in Chinese) Google Scholar
  14. 14.
    Wen J, Wu K, Jin J et al (2006) Combined weight method for rural drinking water insurance evaluation based on information entropy. J Irrig Drain 25(4):43–47 (in Chinese) Google Scholar
  15. 15.
    Jinghua Ma, Xiufang Jia (2013) Comprehensive evaluation of power quality based on the method of consistent between subjective and objective in the least-squares sense. Electr Power Sci Eng 29(4):18–23 (in Chinese) Google Scholar
  16. 16.
    Beynon M, Curry B, Morgan P (2000) The Dempster-Shafer theory of evidence: an alternative approach to multicriteria decision modelling. Omega 28(1):37–50CrossRefGoogle Scholar
  17. 17.
    Li Y, Kang J, Xie H (2011) The algorithm aiming at conflict to improve DS evidence theory. Inf Technol J 10(9):1779–1783CrossRefGoogle Scholar
  18. 18.
    Kaihong Guo, Wenli Li (2011) Combination rule of D-S evidence theory based on the strategy of cross merging between evidences. Expert Syst Appl 38(10):13360–13366CrossRefGoogle Scholar
  19. 19.
    Huynh VN, Nakamori Y, Ho TB et al (2006) Multiple-attribute decision making under uncertainty: the evidential reasoning approach revisited. IEEE Trans Syst Man Cybern Part A 36(4):804–822CrossRefGoogle Scholar
  20. 20.
    Smarandache F, Dezert J (2006) Proportional conflict redistribution rules for information fusion. Smarandache F, Dezert J (ed) vol 2. American Research Press, Rohoboth, pp 3–68Google Scholar
  21. 21.
    Wang Y, Dang Y (2009) Approach to interval numbers investment decision-making based on grey incidence coefficients and D-S theory of evidence. Syst Eng Theory Pract 29(11):128–134 (in Chinese) CrossRefGoogle Scholar
  22. 22.
    Zhong D, Guo X, Li M et al (2007) Parametric design and schemes optimization for underground structure based on 3D geological model. J Tianjin Univ Sci Technol 40(5):519–524 (in Chinese) Google Scholar
  23. 23.
    Wang K, Song H (2003) Comparative analysis of three kinds of objective weight weighting method. Technoecon Manag Res 6:48–49 (in Chinese) Google Scholar
  24. 24.
    Shafer G (1976) A mathematical theory of evidence. Princeton University Press, PrincetonzbMATHGoogle Scholar

Copyright information

© Tianjin University and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.State Key Laboratory of Hydraulic Engineering Simulation and SafetyTianjin UniversityTianjinChina

Personalised recommendations