Research On The Method And Application Of Intuitionistic Fuzzy Multiple Attributes Decision Making Considering Attribute Relevance

With the development of society and economy,the relationship between the objective things has become complex.Coupled with the fuzziness of human thinking,the decision-making environment faced by people has become more complex,fuzzy and related.The disadvantages of the traditional multi-attribute decision-making models based on clear number and attribute independence assumption have become increasingly significant.Intuitionistic fuzzy sets can effectively describe the fuzzy information;the multi-attribute decision-making models considering attribute relevance can depict and integrate the correlation in the decision-making process.The fusion research of the two can effectively make up for the result distortion caused by the information fuzziness and attribute relevance,which has strong academic value and application prospect.In the correlated multi-attribute decision-making problems,the identification,measurement and organic integration of attribute correlation is the key to improve the decision performance.Aiming at improving the scientificity of imformation description and aggregation,this paper conducts research from two aspects: partial attribute correlation and all attribute correlation.Firstly,in order to explore the influence mechanism of attribute relevance on decision-making process and results when partial attributes are related,this paper refines the influence laws of the attribute relevance on VIKOR decision value,proposes a new correlated triangular intuitionistic fuzzy multi-attribute decision-making model and verifies its validity by example analysis.Secondly,in order to explore the rationality of the relevant information aggregation process when all the attributes are related,this paper proves the advantages of Zhenyuan integral in solving correlated multi-attribute decision-making problems,proposes interval-valued intuitionistic fuzzy Zhenyuan operators,designs a new correlated interval-valued intuitionistic fuzzy multi-attribute decision-making model and verifies its effectiveness by example analysis.Finally,the two models are applied to the evaluation of talent agglomeration effect based on industry-university-research cooperative innovation to show their advantages.The main research results of this paper are as follows:(1)In the case of partial attribute correlation,this paper summarizes 4 influence laws of the type and size of attribute relevance on VIKOR group utility value and individual regret value through mathematical derivation,designs a new correlated triangular intuitionistic fuzzy multi-attribute decision-making model based on 2-additive Choquet integral and proves that the method can integrate attribute relevance,simplify compromise solutions and improve the scheme discrimination.(2)In the case of all attribute correlation,this paper proposes interval-valued intuitionistic fuzzy Zhenyuan averaging operator and geometric operator and verifies 5desirable properties of the two operators.A new correlated interval-valued intuitionistic fuzzy multi-attribute decision-making model based on Zhenyuan integral is designed and verified that it can comprehensively aggregate the attribute interaction,effectively reduce the information loss,and improve the accuracy and sensitivity of information integration results.(3)Given that both of the above situations may occur,this paper constructs a talent agglomeration evaluation system based on industry-university-research cooperative innovation,and uses the proposed 2 intuitionistic fuzzy multi-attribute decision-making methods considering attribute relevance to evaluate the reginal talent agglomeration effect.