Research On The Intuitionistic Fuzzy Representation Method Of Multisource And Heterogeneous Decision Information And Its Extension

Driven by the digitalisation process,big data technology has flourished,and the fusion and evaluation of data information has become one of the current research hotspots and has been widely applied to various realistic multi-attribute decision-making problems.With the increasing amount of data,the variability of data sets in terms of data type,data source and data quality in different decision-making environments is gradually increasing.Thus,how to quickly and accurately characterise large-scale decision information scientifically becomes the key to improving the rationality and effectiveness of decision making.To this end,this paper investigates the intuitionistic fuzzy representation of multi-source heterogeneous decision information in the context of big data based on intuitionistic fuzzy theory.The main research work and results of this paper are as follows:(1)An efficient interval intuitionistic fuzzy representation algorithm is proposed for the aggregation problem of multi-source heterogeneous decision information.The algorithm is suitable for heterogeneous data environments with real numbers,interval numbers,triangular fuzzy numbers,trapezoidal fuzzy numbers,linguistic values and intuitionistic fuzzy numbers,and effectively solves the problem of fusion of different types of attribute data.The effectiveness and rationality of the proposed method is verified by taking the environmental index assessment of a provincial capital city in the northwest region as an example.The experimental results show that the algorithm can not only effectively overcome the representation defects of existing methods,but also achieve fuzzy dimensionality reduction aggregation of heterogeneous data and improve the fusion efficiency and accuracy of heterogeneous data.(2)Construct a linguistic intuition fuzzy information representation method to effectively aggregate linguistic evaluation values in a multigranularity linguistic information environment.Firstly,the linguistic term sets of different granularities are pre-processed by defining consistent mapping relations.Then an effective conversion of linguistic intuitionistic fuzzy numbers is achieved based on the linguistic evaluation distance,linguistic evaluation degree and linguistic information normalisation process.Finally,based on the new linguistic intuitionistic fuzzy assignment formula,a linguistic intuitionistic fuzzy representation algorithm in a multi-granularity linguistic information environment is established,and the rationality and feasibility of the proposed algorithm is verified through arithmetic examples.(3)An improved intuitionistic fuzzy representation method based on the golden partition theory is proposed.Firstly,the set of decision information is divided according to the golden partition point,and then the mapping transformation from large-scale real values to single intuitionistic fuzzy numbers is realized based on the distance measure and the normalization method that considers the amount of data in the set.Finally,the characterisation method is applied to the air quality evaluation of various prefecture-level cities in Fujian Province.The results show that the method can achieve effective characterization of large-scale data,thus providing scientific basis and data support for air pollution control and improvement in Fujian Province.