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基于未确知网络分析法的堤防工程风险分析研究
引用本文:李锋,李宗坤. 基于未确知网络分析法的堤防工程风险分析研究[J]. 长江科学院院报, 2012, 29(7): 35-40. DOI: 10.3969/j.issn.1001-5485.2012.07.008
作者姓名:李锋  李宗坤
作者单位:1.郑州大学 水利与环境学院,郑州450002;2.河南省水利科学研究院 河南省水利工程安全技术重点实验室,郑州450003
摘    要:堤防工程是我国防洪体系的重要组成部分。在堤防的运行和管理过程中,各种不确定性因素引起的风险正逐渐引起人们的关注。在对这些风险因子识别和分析的过程中,由于人们认识水平的局限所引起的主观上的不确定性,是堤防工程风险评价的难点之一。考虑到人对影响因素间比较判断的主观性和未确知性,结合未确知测度及网络分析法,提出了基于未确知网络分析法模型理论的堤防工程风险分析方法,并对模型的原理及求解进行了详细的阐述。最后,以某堤防工程为算例,验证了该方法在堤防工程风险评价中应用的科学性。研究成果为堤防工程的风险控制和管理提供了重要的参考。

关 键 词:风险分析  未确知测度  网络分析法  置信度  
收稿时间:2011-06-20

Risk Assessment for Levee Engineering Based on Unascertained Measure and Analytic Network Process
LI Feng , LI Zong-kun. Risk Assessment for Levee Engineering Based on Unascertained Measure and Analytic Network Process[J]. Journal of Yangtze River Scientific Research Institute, 2012, 29(7): 35-40. DOI: 10.3969/j.issn.1001-5485.2012.07.008
Authors:LI Feng    LI Zong-kun
Affiliation:1.School of Water Conservancy and Environmental Engineering, Zhengzhou University,Zhengzhou450002,China; 2.Henan Provincial Key laboratory of Safety Technology for HydropowerEngineering, Henan Provincial Water Conservancy Research Institute, Zhengzhou450003,China
Abstract:Identifying and analyzing risk factors for levee is an important part of flood control system in China.The subjective uncertainty in human recognition is a challenge for levee risk assessment.Based on unascertained measure theory and analytic network process,we presented a risk analysis model for levee engineering,and expounded the principles and solution of the model in details.With a levee project as an example,we established a risk index system,determined the weights of indexes,and calculated the possibility of risk in accordance with the confidence level.The measure space of unascertained ANP assessment model conformed with the normalized and additive condition.The model was confirmed to be credible and could be regarded as important basis for the risk control and management of levee.
Keywords:risk assessment  unascertained measure  ANP(Analytic Network Process)  confidence level
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