Affiliations: [a] Information Science and Engineering, Northeastern University, Heping District Shenyang, Liaoning, China | [b] State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Heping District Shenyang, Liaoning, China | [c] BGRIMM Technology Group, Daxing District, Beijing, China
Correspondence:
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Corresponding author: Fuli Wang, Information Science and Engineering, Northeastern University, P.O.Box 135, No.11 St.3 Wenhua Road, Heping District Shenyang, Liaoning 110819, China. Tel.: +86 13840032743; E-mail: [email protected].
Abstract: For the Bayesian network (BN) structure learning, the key problem is to determine the relationship between the BN nodes. In this paper, the scheme of group decision making (GDM) based on the intuitionistic fuzzy set for the relationship determination between the BN nodes is proposed. Firstly, the alternative relationships between the BN nodes are analyzed. The relationship determination problem is transformed into the GDM problem. Furthermore, the specific GDM scheme is proposed to determine the relationship. Finally, the proposed scheme is applied to establish the model for the thickening process of gold hydrometallurgy. For the different conditions of group expert knowledge including the consistent and inconsistent information, the process of GDM is shown, and the aggregation results of different aggregation operators and the influence of hesitancy degree are analyzed. We can conclude that the expert who owns bigger membership degree and less hesitancy degree plays the most important role in the process of decision making.
Keywords: Bayesian network, relationship determination, group decision making, expert knowledge, intuitionistic fuzzy set, inconsistent information
