基于语言值聚合算法的数据去重产品选择
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摘要
针对语言真值直觉模糊信息环境下的数据去重产品选择问题,构建了一种基于语言真值直觉模糊集成算法的多属性决策方法。该方法首先在语言真值直觉模糊代数的基础上,运用语言真值直觉模糊对来表达既有可比性又有不可比性的模糊语言值信息;其次提出了语言真值直觉模糊加权平均算子和语言真值直觉模糊有序加权平均算子,并讨论了其相关性质,同时利用两种聚合算子对语言真值直觉模糊信息进行加权聚合,将聚合结果进行排序;然后引入了参照相近度用以处理排序过程中出现的不可比情况;最后构建一种语言真值直觉模糊多属性群决策方法,并通过数据去重产品的选择实例说明提出的决策方法是合理和有效的。
For the data deduplication product selection problem under the linguistic truth-valued intuitionistic fuzzy information environment,a novel multi-attribute decision making method based on the linguistic truth-valued intuitionistic fuzzy aggregation algorithm is investigated.First,based on the linguistic truth-valued intuitionistic fuzzy algebra,the linguistic truth-valued intuitionistic fuzzy pairs are utilized to express the fuzzy linguistic-valued information which is both comparable and incomparable.Then,the linguistic truth-valued intuitionistic fuzzy weighted averaging operator and linguistic truth-valued intuitionistic fuzzy ordered weighted averaging operator are proposed,and their properties are discussed in detail.Fuzzy linguistic-valued information is weighted and aggregated by two aggregation operators,and the aggregation results will be ranked.In addition,the reference nearness degree is introduced for the situation of incomparability in the process of ranking.Finally,a linguistic truth-valued intuitionistic fuzzy multi-attribute decision making method is developed,and the developed method is applied to research the data deduplication product selection to demonstrate its rationality and effectiveness.
For the data deduplication product selection problem under the linguistic truth-valued intuitionistic fuzzy information environment,a novel multi-attribute decision making method based on the linguistic truth-valued intuitionistic fuzzy aggregation algorithm is investigated.First,based on the linguistic truth-valued intuitionistic fuzzy algebra,the linguistic truth-valued intuitionistic fuzzy pairs are utilized to express the fuzzy linguistic-valued information which is both comparable and incomparable.Then,the linguistic truth-valued intuitionistic fuzzy weighted averaging operator and linguistic truth-valued intuitionistic fuzzy ordered weighted averaging operator are proposed,and their properties are discussed in detail.Fuzzy linguistic-valued information is weighted and aggregated by two aggregation operators,and the aggregation results will be ranked.In addition,the reference nearness degree is introduced for the situation of incomparability in the process of ranking.Finally,a linguistic truth-valued intuitionistic fuzzy multi-attribute decision making method is developed,and the developed method is applied to research the data deduplication product selection to demonstrate its rationality and effectiveness.
引文
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[2]Hermosilla T,Wulder M A,White J C,et al.Mass data processing of time series Landsat imagery:pixels to data products for forest monitoring[J].International Journal of Digital Earth,2016:1-20.
[3]聂东明.群决策中犹豫乘性偏好关系一致性修复方法[J].控制工程,2016,23(4):623-628.Nie D M.Method for repairing the consistency of hesitant multiplicative preference relations in group decision making[J].Control Engineering of China,2016,23(4):623-628.
[4]Zadeh L A.Fuzzy sets[J].Information and Control,1965,8(3):338-353.
[5]Xu Z S,Zhao N.Information fusion for intuitionistic fuzzy decision making:an overview[J].Information Fusion,2016,28(2):10-23.
[6]Xu Z S.Additive intuitionistic fuzzy aggregation operators based on fuzzy measure[J].International Journal of Uncertainty,Fuzziness and Knowledge-Based Systems,2016,24(1):1-12.
[7]Atanassov K T.Intuitionistic fuzzy sets[J].Fuzzy Sets and Systems,1986,20(1):87-96.
[8]高建伟,刘慧晖,谷云东.基于前景理论的区间直觉模糊多准则决策方法[J].系统工程理论与实践,2014,34(12):3175-3181.Gao W J,Liu H H,Gu Y D.Interval-valued intuitionistic fuzzy multi-criteria decision-making method based on prospect theory[J].Systems Engineering-Theory&Practice,2014,34(12):3175-3181.
[9]周晓辉,姚俭.区间直觉梯形模糊几何Heronian平均算子及应用[J].计算机工程与应用,2016,52(9):39-43.Zhou X H,Yao J.Interval-valued intuitionistic trapezoidal geometric Heronian means operator and its application[J].Computer Engineering and Applications,2016,52(9):39-43.
[10]Lei Q,Xu Z S,Humberto B,et al.Intuitionistic fuzzy integrals based on archimedean T-conorms and T-norms[J].Information Sciences,2016,327(2):57-70.
[11]Xu Z S,Zhao N.Information fusion for intuitionistic fuzzy decision making:an overview[J].Information Fusion,2016,28(1):10-23.
[12]Xu Y,Ma J.Linguistic truth-valued lattice implication algebra and its properties[J].The Proceedings of the IMACS Multi-Conference on Computational Engineering in Systems Applications,2006,2(7):1413-1418.
[13]Li Z,Liu X,Zheng P,et al.Implication operators on the set of V-irreducible element in the linguistic truth-valued intuitionistic fuzzy lattice[J].International Journal of Machine Learning and Cybernetics,2013,4(4):365-372.
[14]Rodriguez R M,Martinez L,Herrera F,et al.A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets[J].Information Sciences,2013,241(3):28-42.
[15]Luo X D,Zhong Q T,Leung H F,et al.A spectrum of weighted compromise aggregation operators:a generalization of weighted uninorm operator[J].International Journal of Intelligent Systems,2015,30(12):1185-1226.
[16]Yager R R.On ordered weighted averaging aggregation operators in multicriteria decision making[J].IEEE Transactions on Systems,Man,and Cybernetics,1988,18(1):183-190.
[17]Xu Z S.Intuitionistic fuzzy aggregation operators[J].IEEE Transactions on Fuzzy Systems,2007,15(6):1179-1187.
[18]张焕君,杨小宁.基于模糊聚类分析的临床路径决策研究[J].控制工程,2013,20(6):1118-1122.Zhang H J,Yang X N.Based on the fuzzy clustering analysis of clinical pathway decision research[J].Control Engineering of China,2013,20(6):1118-1122.
[19]Zhu H,Zhao J,Xu Y,et al.2-Dimension linguistic computational model with 2-tuples for multi-attribute group decision making[J].Knowledge-Based Systems,2016,103(6):132-142.
[20]徐胜军,韩九强,刘光辉,等.基于马尔可夫随机场的图像分割算法综述[J].计算机应用研究,2013,30(9):2576-2582.Xu S J,Han J Q,Liu G H,et al.Survey of image segmentation methods based on Markov random fields[J].Application Research of Computers,2013,30(9):2576-2582.