云模型理论在区域旱涝评价中的应用  

Assessment Model of Drought and Waterlogging with Could Model

作　　者：张明媛[1] 高盼[1] 袁永博[1] 

机构地区：[1]大连理工大学建设工程学部建设管理系,辽宁大连116024

出　　处：《模糊系统与数学》2016年第1期174-181,共8页Fuzzy Systems and Mathematics

基　　金：国家自然科学基金资助项目(51208081);辽宁省高等学校科研计划项目(L2014034)

摘　　要：评价具有不确定性,而这种不确定性主要表现在模糊性和随机性上面;云模型可将模糊性和随机性集结在一起,实现定量数值与定性语言之间的自然映射。本文利用云模型的正向云发生器和逆向云发生器对山东省旱涝情况进行综合评价,在建立评价云时,根据评价等级划分原理,利用逆向云发生器来确定评价云中超熵的值,使评价云更加客观,且评价过程不对原始数据进行标准化或归一化处理,避免了数据再处理过程中可能出现的信息丢失。利用该方法不仅可以得到合理的评价结果,而且能够给出评价结果相应的稳定性大小,模型算法简单,适应性较强,并且易于编程实现,最后本文将云模型评价结果与模糊综合评价结果进行比较,进一步验证了基于云模型旱涝评价的可行性和合理性。Evaluation has great uncertainty which is mainly manifested in fuzziness and randomness.The cloud model can gather the fuzziness and randomness together to realize the natural mapping between quantitative numberical and qualitative language.Based on Forward Cloud Generator and Backward Cloud Generator,thia paper evaluates drought and waterlogging situation in Shangdong Province.In the establishment of the evaluation of the cloud,according to the classification principle of the evaluation grade,the value of the hyper entropy in the cloud model is determined by the Backward Cloud Generator,which makes the evaluation cloud more objective.Evaluation precess does not standardize and normalize the original data,which avoids the possibility of information loss during data reprocessing.The evaluation model not only obtains reasonable assessment result but also provides the credibilty information of the evaluation result.The model algorithm in this research was simple,strong adaptability,and easy to program.Comparison with other evaluation results validated feasibility and reasonableness of drought and waterlogging evaluation method based on the cloud model.

关 键 词：云模型 旱涝评价 模糊性 随机性 

分 类 号：O159[理学—数学]