A novel rough set approach is proposed in this paper to discover classification rules through a process of knowledge induction which selects optimal decision rules with a minimal set of features necessary and sufficient for classification of real-valued data. A rough set knowledge discovery...

Building a feedforward computational neural network model (CNN) involves two distinct tasks: determination of the network topology and weight estimation. The specification of a problem adequate network topology is a key issue and the primary focus of this contribution. Up to now, this issue has...

Reference control points (RCPs) used in establishing the regression model in the registration or geometric correction of remote sensing images are generally assumed to be ?perfect?. That is, the RCPs, as explanatory variables in the regression equation, are accurate and the coordinates of their...

A novel rough set approach is proposed in this paper to discover classification rules through a process of knowledge induction which selects decision rules with a minimal set of features for classification of real-valued data. A rough set knowledge discovery framework is formulated for the...