Research On The Expansion Model Of Rough Set In Incomplete Decision Information Systems

This paper researches on incomplete decision information system by the tool of rough set theory, and improves there existing models in the system.First, in the incomplete decision information system, rough set model based on limited tolerance relationcan't deal with the incompatibility caused by information or the data with noise. It can't get probabilistic decision rules, too. According to this problem, we introduce inclusion degree, put forward variable rough set modelbased on limited tolerance relation.Second, in theincomplete information preference multi-attribute decision system, rough set model based on limited extended dominance relation andrough set model based onlimited advantage relationcan't deal with the incompatibility caused by information or the data with noise or get probabilistic decision rules. According to this problem, we bring in inclusion degree, and put forward variable rough set modelbased onlimited extended dominance relation and variable rough set modelbased onlimited advantage relation, respectively.At last, we research on the properties of the improved models, and compare them with the original models. We make knowledge reduction and rule extraction, and prove that our theories and methods are practicable by example verification.