摘要
提出了模糊划分的一个新定义。可以证明它蕴含了Ruspini的定义 ,并且具有与直观及其实际应用相符的性质。而且根据此定义 ,可以定义模糊集合的相对清晰度及模糊划分的平均清晰度。实验证明 ,模糊划分的平均清晰度可以衡量FCM算法的聚类效果。
In this paper, we pointed out that the Ruspini's definition of fuzzy pa rtition h as a shortcoming, which does not always coincide with our intuition. So we propo s ed a new definition for fuzzy partition and proved the new definition of fuzzy partition has a desired property consistent with our intuition and applications of fuzzy partition (e.g., fuzzy decision making, fuzzy clustering, fuzzy control , etc.). It can follow Ruspini's definition of fuzzy partition, which are cited frequently in current papers. According to the new definition of fuzzy partition , we defined the relative clearness of fuzzy sets and the mean clearness of fuzz y partition. The latter is proved effective for evaluating the performance of FC M algorithm by the experiments.
出处
《北京大学学报（自然科学版）》
CAS
CSCD
北大核心
2000年第5期619-623,共5页
Acta Scientiarum Naturalium Universitatis Pekinensis
基金
国家自然科学基金资助项目!(6 9872 0 0 3)
