| Abstract | Information granulation is very essential to human problem solving,
and hence has a significant impact on the design and implementation of
intelligent systems. Most granulation methods did not go deep in using topological
structure. In this work, we aim to use general topological structures as
tools for decision making in multi-valued information systems “MVIS”. General
relations are used to get granules that form subbase for topologies. These
topologies are applied for obtaining discernibility matrix and reducts. The
suggested topological structures open up the way for applying rich amount of
topological facts and methods in the process of granular computing. |