This paper introduces a neural network architecture based on rough sets and rough membership functions. The neurons of such networks instantiate approximate reasoning in assessing ...
James F. Peters, Andrzej Skowron, Liting Han, Shee...
This paper introduces the design of rough neurons based on rough sets. Rough neurons instantiate approximate reasoning in assessing knowledge gleaned from input data. Each neuron c...
James F. Peters, Andrzej Skowron, Zbigniew Suraj, ...
Rough set theory has been considered as a useful tool to deal with inexact, uncertain, or vague knowledge. However, in real-world, most of information systems are based on dominanc...
Interval computations estimate the uncertainty of the result of data processing in situations in which we only know the upper bounds ∆ on the measurement errors. In interval comp...