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大坝渗流安全综合评价的评价指标赋权方式多基于专家群决策方法，此方法没有考虑人为决策时存在的犹豫心理和不确定性问题。为此，提出了一种基于犹豫云语言术语集的专家群决策主观赋权法。通过构建犹豫模糊术语集，并将之转化为犹豫云模型，使得专家在决策时可以同时给出数个犹豫云评价术语，解决了人为决策时存在的犹豫性和不确定性问题。同时，采用基于加速遗传算法优化的投影寻踪客观赋权法和基于最小相对熵原理耦合主客观赋权的综合赋权方法，并结合有限区间云模型构建完整的土石坝渗流安全评价方法。案例分析表明：基于犹豫云语言术语集的专家群决策主观赋权法相较于传统主观赋权方法可以更好地表达犹豫信息，其评价结果可以较为真实地反映西南某水电站的渗流安全状态，为实际工程管理提供依据。
Abstract：At present, the weighting modes of the evaluation indexes for the comprehensive assessment on the seepage safety of earth-rockfill dam are mostly based on expert group decision-making method without the consideration of hesitation and uncertainty during human decision-making. Therefore, a hesitant cloud linguistic term set-based expert group decision-making subjective weighting method is proposed herein. Through constructing hesitation fuzzy term set and transforming it into hesitation cloud model, this method makes experts give several hesitant cloud evaluation terms simultaneously during the relevant decision-making, and thus solves the problem of the hesitation and uncertainty during human decision-making. Additionally, the accelerated genetic algorithm optimization-based projection pursuit objective weighting method and the minimum relative entropy principle coupled subjective and objective weighting-based comprehensive weighting method are adopted to construct a complete seepage safety evaluation method for earth rockill dam in combination with finite interval cloud model. The relevant case analysis shows that the related hesitation information can be better expressed by the hesitant cloud linguistic term set-based expert group decision-making subjective weighting method if compared with that from the conventional subjective weighting method, and then its evaluation result can more truly reflect the seepage safety state of a hydropower station in southwest China, thus provides a basis for the actual project management concerned.
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基本信息:
DOI：10.13928/j.cnki.wrahe.2022.10.012
中图分类号:TV223.4;TV641
引用信息:
[1]程正飞,喻葭临,郑鸣蔚,等.土石坝渗流安全犹豫云语言术语集评价研究[J],2022,53(10):155-164.DOI:10.13928/j.cnki.wrahe.2022.10.012.
基金信息:
国家自然科学基金项目(59035679);; 2002年高等学校博士学科点专项科研项目(20020183061)