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区间数直觉模糊多属性决策的联系数新算法 被引量:1

A New Algorithm for Interval Intuitionistic Fuzzy Multiple-attribute Decision Making Based on Connection Number
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摘要 针对区间直觉模糊多属性决策的模糊不确定问题,提出一种基于联系数的区间直觉模糊多属性决策新算法。首先把区间数转换成a+bi型的二元联系数,把区间直觉模糊数转换为a+bi形式的直觉模糊数;再参照三元联系数的势函数概念计算直觉模糊数的直觉模糊势,建立基于直觉模糊势的多属性决策模型,依据模型中的综合加权直觉势大小得出n个方案的初排序,依据模型中的综合加权模糊势做初排序的不确定性分析得到终排序。实例应用结果证实了新算法思路的合理性和结果的有效性。 Aiming at the fuzzy uncertainty of interval intuitionistic fuzzy multi-attribute decision making,a new algorithm for interval intuitionistic fuzzy multi-attribute decision-making based on connection number is proposed.Firstly,interval number is transformed into binary connection number of type a+bi,and interval intuitionistic fuzzy number is transformed into intuitionistic fuzzy number of type a+bi.Then the intuitionistic fuzzy potential of intuitionistic fuzzy number is calculated with reference to the concept of potential function of ternary connection number;a multi-attribute decision making model based on intuitionistic fuzzy potential is established;the initial ranking of numerous solutions is obtained based on the integrated weighted intuitionistic potential size in the model,and the final ranking is obtained based on the integrated weighted fuzzy potential in the model.The uncertainty analysis of the initial ranking is done to obtain the final ranking.The results of the practical application prove the rationality of the new algorithm idea and the effectiveness of the results..
作者 陆广地 LU Guang-di(Jiangsu United Vocational and Technical College,Shuyang,Jiangsu 223600,China;Jiangsu University of Science and Technology,Zhenjiang,Jiangsu 215600,China)
出处 《邢台职业技术学院学报》 2023年第1期76-84,共9页 Journal of Xingtai Polytechnic College
基金 国家陶研会立项课题--“创客教育实践研究”,编号:TD2017203 宿迁市社科2022立项课题--“产教结合推进文化创意产业群建设实践研究”编号:22/B/39。
关键词 区间直觉模糊数 区间直觉模糊多属性决策 联系数 直觉模糊势 不确定性示性系数 不确定性分析 interval intuitionistic fuzzy number interval intuitionistic fuzzy multi-attribute decision making:binary connection number ternary connection number intuitionistic fuzzy potential uncertainty indicative coefficient uncertainty analysis
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