The paper draws comparison and analysis among present similarity measure methods in the case of similari-ty measures between Vague values, provides a new similarity measure method, of which discusses on the normalchar...The paper draws comparison and analysis among present similarity measure methods in the case of similari-ty measures between Vague values, provides a new similarity measure method, of which discusses on the normalcharacteristics, gives some relative character theorems. At the same time, it analyzes the application of fuzzy similari-ty measures in vague similarity measures and gives its normal forms such as similarity measures between Vague sets,between elements and their weighted similarity measures. Finally, vague entropy rule respectively aiming at twokinds of cases is approached and its corresponding vague entropy expressions is provided. The content of this paper isof practical significance in such fields as fuzzy decision-making, vague clustering, pattern recognition, data miningetc.展开更多
在毕达哥拉斯犹豫模糊数的距离基础上,定义毕达哥拉斯犹豫模糊集(Pythagorean hesitant fussy set,PHFS)的加权距离测度和有序加权距离测度,在兼顾属性权重和位置权重的基础上,提出广义PHFS混合加权距离测度(D_(GPHFHWA)),并研究其性质...在毕达哥拉斯犹豫模糊数的距离基础上,定义毕达哥拉斯犹豫模糊集(Pythagorean hesitant fussy set,PHFS)的加权距离测度和有序加权距离测度,在兼顾属性权重和位置权重的基础上,提出广义PHFS混合加权距离测度(D_(GPHFHWA)),并研究其性质和特殊形式。针对属性值为毕达哥拉斯犹豫模糊数且属性权重未知的多属性决策问题,利用毕达哥拉斯犹豫模糊指数熵确定属性权重,并结合逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)思想,提出基于D_(GPHFHWA)测度的决策方法。最后,通过实例验证所提方法是有效、合理的。展开更多
文摘The paper draws comparison and analysis among present similarity measure methods in the case of similari-ty measures between Vague values, provides a new similarity measure method, of which discusses on the normalcharacteristics, gives some relative character theorems. At the same time, it analyzes the application of fuzzy similari-ty measures in vague similarity measures and gives its normal forms such as similarity measures between Vague sets,between elements and their weighted similarity measures. Finally, vague entropy rule respectively aiming at twokinds of cases is approached and its corresponding vague entropy expressions is provided. The content of this paper isof practical significance in such fields as fuzzy decision-making, vague clustering, pattern recognition, data miningetc.
文摘在毕达哥拉斯犹豫模糊数的距离基础上,定义毕达哥拉斯犹豫模糊集(Pythagorean hesitant fussy set,PHFS)的加权距离测度和有序加权距离测度,在兼顾属性权重和位置权重的基础上,提出广义PHFS混合加权距离测度(D_(GPHFHWA)),并研究其性质和特殊形式。针对属性值为毕达哥拉斯犹豫模糊数且属性权重未知的多属性决策问题,利用毕达哥拉斯犹豫模糊指数熵确定属性权重,并结合逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)思想,提出基于D_(GPHFHWA)测度的决策方法。最后,通过实例验证所提方法是有效、合理的。
