关键词: 直觉模糊向量, 关联规则挖掘, 双重模糊变量, 双重模糊模拟, 犹豫度

Abstract: For the inadequacies of traditional fuzzy association rules mining in primary decision tables and mining algorithm,a new method of intuitionistic fuzzy vector association rules mining based on dual fuzzy simulation was proposed.Aiming at the deficiency of traditional fuzzy association rules mining to express the hesitation of decision makers and the multiple dimensions of natural language in primary decision aspect,the intuitionistic fuzzy vectors composed by intuitionistic fuzzy sets were adopted to construct the primary decision table.Considering expression habits of decision makers,dual fuzzy variable were adapted to model intuitionistic fuzzy set,in which the hesitation had been modeled as fuzzy sets.From the aspect of mining algorithm,the following two problems should be solved during intuitionistic fuzzy vector association rules mining: the low efficiency of the algorithm caused by huge dimension of primary decision table;the hesitation degree of intuitionistic fuzzy set could not be computed by exist algorithm.Hierarchical frame was constructed to solve sparseness of decision matrix,in which antecedent's dimensionality was reduced by the bottom level association rules mining method,so as to increase the digging efficiency.Dual fuzzy simulation was introduced to integrate hesitancy degree of intuitionistic fuzzy sets when in the support degree.A case of naked eye 3D movies making process was highlighted to show the effectiveness and feasibility of proposed method.

Key words: intuitionistic fuzzy vector, association rules mining, dual fuzzy variable, dual fuzzy simulation, hesitancy degree