Improved catastrophe theory evaluation method and its application to earth-rock dam risk evaluation during construction

被引:0
作者
Li, Zong-Kun [1 ]
Ge, Wei [1 ]
Wang, Juan [1 ]
Guo, Wei-Wei [1 ]
机构
[1] Zhengzhou University, Zhengzhou
来源
Shuili Xuebao/Journal of Hydraulic Engineering | 2014年 / 45卷 / 10期
关键词
Catastrophe theory evaluation method; Earth-rock dam construction; Hydraulic structure; Improvement; Risk evaluation;
D O I
10.13243/j.cnki.slxb.2014.10.015
中图分类号
学科分类号
摘要
There are two major problems identified in the application of conventional catastrophe theory evaluation method: (a) overestimated assessment values and (b) the indistinguishability of the final values from both prior and inferior projects. In order to solve the above-mentioned drawbacks, an improved catastrophe theory evaluation method is proposed in this paper. In this method, an S-curved distribution is incorporated as a fitting function. The initial comprehensive evaluation value is mapped to the underlying index membership to acquire improved value of catastrophe theory evaluation method, effectively expanding the scope of the distribution and dramatically clarifying the merits of the evaluation. Through empirical analysis and applying the method to risk evaluation and comparison of the construction program of Yanshan Reservoir, the author verifies rationality of the proposed methods, which preferably offer instructions to engineering construction. ©, 2014, China Water Power Press. All right reserved.
引用
收藏
页码:1256 / 1260
页数:4
相关论文
共 4 条
[1]  
Krimsky S., The Role of Theory in Risk Studies in Sheldon Krimsky and Dominic Golding, Eds, (2005)
[2]  
Poston T., Catastrophe Theory and Its Applications , (1996)
[3]  
Zhao Z., Ling W., Zillante G., An evaluation of Chinese Wind Turbine Manufacturers using the enterprise niche theory , Renewable and Sustainable Energy Reviews, 16, 1, pp. 725-734, (2012)
[4]  
Su S., Zhang Z., Xiao R., Et al., Geospatial assessment of agroecosystem health: Development of an integrated index based on catastrophe theory, Stochastic Environmental Research and Risk Assessment, 26, 3, pp. 321-334, (2012)