Fuzzy Rough Set Model Based On Sugeno Measure

Pawlak fuzzy rough set model is based on the probability measure ,while the condition of additively is too harsh and the equivalence relation in probabilistic rough set model too strict, limit the application of its. Sugeno measure is highly representative of the non-additive measure, it is the probability for promotion, and while the reverse and similar relationship is non-equivalence relationship has a broad application. Based on this, fuzzy rough set model based on Sugeno measure, Sugeno measure fuzzy rough set model under reverse relationship and Sugeno measure fuzzy rough set model under similar relationship is proposed. The properties underlying the unions, intersections, and complements of those upper-approximations and lower-approximations are provided; Moreover, cut sets of corresponding model are given; finally, we define the approximation accuracy and roughness of the three models.