论文部分内容阅读
鉴于典型暴雨在资料缺乏的中小流域水文设计时的重要性,考虑到典型暴雨本身具有灰色性、模糊性及随机性,从水文设计的安全性与样本集的整体性考虑,确定能反映暴雨特性的因子指标,采用可能度法计算各指标的权重,在典型暴雨灰加权关联度综合评价模型、典型暴雨模糊加权模式识别模型及典型暴雨贝叶斯加权评价模型三个单一模型的基础上,构建了基于贝叶斯理论的典型暴雨灰色模糊优选综合模型,以优选典型暴雨。实例应用结果表明,单一模型及综合模型均给出了选择典型暴雨的定量计算方法,得到了典型暴雨的可行性解集,弥补了传统定性选择典型暴雨主观随意性较大的不足,其中综合模型得到的可行性解集更可靠,解集中各元素的离散程度大,更便于典型暴雨的优选。
Considering the importance of typical storm events in hydrological design of small and medium-sized watersheds lacking in data, taking into account the grayness, fuzziness and randomness of typical stormstorms, the safety of hydrological design and the integrity of sample sets are considered to reflect the characteristics of stormwater , The weight of each index is calculated by the probabilistic method. Based on the three single models of the typical storm-gray weighted relevance degree comprehensive evaluation model, the typical rainstorm fuzzy weighted pattern recognition model and the typical stormy Bayesian weighted evaluation model, Based on the Bayesian theory, a typical storm gray fuzzy optimization model is selected to optimize the typical storm. The results of practical application show that both the single model and the comprehensive model give the quantitative calculation method of selecting typical rainstorms, and the feasible solution set of typical rainstorms is obtained, which makes up for the lack of subjective randomness of typical qualitatively selected heavy rainstorms. The comprehensive model The solution of the feasible solution is more reliable, the dispersion of each element in the solution set is large, and it is more convenient for the selection of the typical rainstorm.