The Evaluation on Development Quality of Open Education Based on Dempster-Shafer With Multigranularity Unbalanced Hesitant Fuzzy Linguistic Information for Chinese Case

Abstract

Multi-granularity unbalanced hesitant fuzzy linguistic term set (MGUHFLTS) is an effective expression of linguistic information, which applied in multi-attribute group decision-making (MAGDM), meanwhile Dempster-Shafer evidence theory (DSET) is profound method of representing and aggregating uncertain information. In order to combine the advantages from both, a new MAGDM approach based on Dempster-Shafer with MGUHFLTSs is proposed. The initial MGUHFLTSs decision matrix is transformed to evidence matrix, and a novel weight determination model of MAGDM problem with MGUHFLTSs is established in this approach. In additional, in order to combine evidence with MGUHFLTSs, a new MAGDM combination algorithm is proposed by means of DSET combination rules, which reduces the loss of MGUHFLTSs information for. An example is applied with this method about evaluation on the development quality of open education. Finally, this paper proves the validity and superiority of the proposed method.

Keywords

• Multiple attribute group decision-making
• multi-granularity hesitant fuzzy linguistic term set
• unbalanced linguistic term set
• Dempster-Shafer evidence theory
• BWM