A Novel Diversified Attribute Group Decision-Making Method Over Multisource Heterogeneous Fuzzy Decision Systems With Its Application to Gout Diagnosis

Group decision making (GDM) is a useful uncertain decision theory and tool. With the evolution of time, GDM problems become more and more complex. In reality, there are plenty of GDM problems with diversified attributes and heterogeneous information. In this article, the diversified attributes describe the differences in attributes given by different decision makers, and heterogeneous information refers to the differences in data types. Nonetheless, few existing GDM studies simultaneously focus on the above two characteristics of GDM problems. Moreover, the scenario of multiple decision preferences and the attribute and expert weights based on heterogeneous information are also seldom discussed. Given this, by considering a kind of GDM problem with the characteristics of multisource, heterogeneity, diversity, and multiple fuzzy decisions, this article builds a novel GDM method from the perspective of multigranulation rough sets. First, we construct a new weighted multigranulation generalized fuzzy rough set (WMGGFRS) over multisource heterogeneous fuzzy decision systems. Subsequently, in response to heterogeneous information, the extended entropy weight methods are given to calculate the weight of each attribute and the weight of each expert. After that, we establish a GDM method using the WMGGFRS model to realize multisource information fusion. Finally, we apply the established method to the management decision-making problem of gout diagnosis. The results of comparative and sensitivity analyses demonstrate the feasibility, effectiveness, stability, and superiority of the method.