摘要
灾情评价实质上是一个模式识别问题。以往的灾情评价模型,虽解决了各单项指标灾情等级评估结果的不相容问题,但往往不能检验所给结果的准确性。基于可变模糊集理论,采用可变模糊评价模型可以科学、合理地确定样本指标对各级指标标准区间的相对隶属度和相对隶属函数,并且能够通过变换参数(α与p)变化模型进行评价。通过对多个评价结果进行比较分析,可以合理地确定出样本的评价等级。同时,由于该模型确定的灾级是连续的实数值,因而提高了灾情等级评价的灾级分辨率。最后将该方法应用于河南省洪涝灾情的综合评价中。应用实例表明,该模型计算简便,评价结果可信度高,可推广应用到其它灾情等级评估中。
It is essentially a problem of pattern recognition to assess flood disaster loss. Although former assessment methods have resolved the non-uniformity problem of evaluation results of disaster loss indexes, they can＇ t test the exactness of the results . Based on the theory of variable fuzzy set, the method and corresponding model for variable fuzzy assessment are established. This method can reasonably identify the relative membership degree between the sample index and standard interval of each level index and properly determine the assessment level of each sample by varying the model and its parameters, so that the reliability of assessment can be improved. The proposed method is applied to assess the loss grade of disaster in Henan Province. The case study verifies that the mentioned method and corresponding model are reliable and easy to be used.
出处
《自然灾害学报》
CSCD
北大核心
2008年第5期34-39,共6页
Journal of Natural Disasters
基金
国家自然科学基金资助项目(50479056)
关键词
灾情评价
模式识别
可变模糊集
相对隶属度
disaster loss evaluation
pattern recognition
variable fuzzy set
relative membership degree
作者简介
张弛（1975-），男，讲师，博士，主要从事水文预报与水库调度研究．E-mail：czhang@dlut．edu.cn
