Research on Evidence Theory Model of Hesitant Fuzzy Information Over Two Universes

Aiming at the computational complexity of generalized two-universe hesitant fuzzy rough set in dealing with complex hesitant information multi-attribute decision making, this paper deeply studies the description and construction of two-universe hesitant fuzzy belief structure based on evidence theory, and proposes a two-universe hesitant fuzzy information multi-attribute decision making algorithm. In this paper, the two-universe hesitant fuzzy approximation operators and the two-universe dual hesitant fuzzy approximation operators are defined, and the corresponding probability measure models are proposed respectively. Secondly, the belief function and plausible function of two-universe hesitant fuzzy information system and two-universe dual hesitant fuzzy information system are defined by using probability measure, and their belief structures were proved theoretically. Finally, according to the proposed evidence theory model, a multi-attribute decision-making algorithm based on two-universe hesitant fuzzy evidence theory is designed. Compared with other literature conclusions, the decision-making algorithm strategy has obvious advantages and the time complexity is significantly reduced. The evidence theory model provides a new idea for hesitant fuzzy information decision-making.