摘要
在对立模糊集定义基础上给出以相对隶属函数表示的模糊可变集合定义,给出可变模糊聚类迭代模型、可变模糊模式识别模型、可变模糊对立识别模型.它们是可变模糊聚类、识别、优选决策、评价相统一的理论模型集,是可变模糊集的基础模型与核心内容,可用于自然、管理、人文、社会等各种学科中关于模糊聚类、识别、优选决策、评价、预测等众多实际领域.
Based on definition of opposite fuzzy sets, the definition of fuzzy variable sets which is expressed by relative membership function and the model of variable fuzzy clustering iteration, variable fuzzy pattern recognition, and variable fuzzy opposite recognition are given in this paper. These are unified model sets for variable fuzzy clustering, recognition, optimum decision making and assessment. More importantly, these are base and core to the theory of variable fuzzy sets. They could be applied to actual problems in all kinds of subject, such as nature, management, humanity and society, etc., including fuzzy clustering, recognition, optimum decision making, assessment and forecasting, etc.
出处
《数学的实践与认识》
CSCD
北大核心
2008年第18期146-153,共8页
Mathematics in Practice and Theory
基金
国家自然科学基金(50779005)
水利部科技创新项目(SCXC2005-01)
关键词
可变模糊集
可变模型集
对立模糊集
模糊聚类
模糊模式识别
模糊优选决策
variable fuzzy sets
variable model sets
opposite fuzzy sets
fuzzy clustering
fuzzy pattern recognition
fuzzy optimum decision making
