一种Vague集相似度量新方法及其应用

分析了影响Vague集相似度量的因素,并充分考虑了未知度对Vague集相似度量的影响,提出了一个新的Vague集相似度量方法,证明该方法满足相似度量的基本准则,通过分析影响相似度量的因素,探讨了现有Vague集相似度量方法存在不足之处,与现有相似度量方法比较证明新的相似度量方法能够有效和合理的区分数据,具有一定的优越性,最后在模式识别的应用实例中,给出了该相似度量方法的模式识别应用过程,实验结果表明了该方法的实用性。

A New Method of Similarity Measure Between Vague Sets and Its Application

Some factor of influencing Vague sets was analyzed.A new method of similarity measure between Vague sets was proposed,the influence of hesitancy degree were considered,and is proved to satisfy some basic rules.Some faults of existed methods of similarity measure between Vague sets were explored by analyzing some factor of influencing Vague sets.Compared with existed methods of similarity measure,new method of similarity measure between Vague sets can reasonably and effectively distinguish data,advantage of this method is illustrated by an example.Finally,the new method of similarity measure between Vague sets was applied to pattern recognition.The results of simulation showed that the method of similarity measure is practicable.