id: 06059006
dt: a
an: 06059006
au: Xu, Weihua; Zhang, Xiantao; Wang, Qiaorong
ti: A generalized multi-granulation rough set approach.
so: Huang, De-Shuang (ed.) et al., Bio-inspired computing and applications. 7th
    international conference on intelligent computing, ICIC 2011,
    Zhengzhou, China, August 11‒14. 2011. Revised selected papers.
    Berlin: Springer (ISBN 978-3-642-24552-7/pbk). Lecture Notes in
    Computer Science 6840. Lecture Notes in Bioinformatics, 681-689 (2012).
py: 2012
pu: Berlin: Springer
la: EN
cc: 
ut: information level; lower and upper approximation sets; multi-granulation
    rough set; supporting characteristic function; majority granulations
ci: 
li: doi:10.1007/978-3-642-24553-4_90
ab: Summary: A generalized multi-granulation rough set is proposed in this
    paper. In the new model, supporting characteristic function is defined
    and a parameter called information level is introduced to investigate
    that an object supports a concept precisely under majority
    granulations. Moreover, some important properties are discussed on the
    new multi-granulation rough set. And it can be found that the proposed
    model is more valid than old multiple granulation rough set models and
    Pawlak rough set model.
rv: