Rough Set Approach to Knowledge Discovery of Process in Process Industry

Rough Set Approach (RSA) has been introduced to deal with multiple attributes reduction and multiple rules extraction for knowledge discovery, where assignments of objects may be inconsistent with respect to consistent principle. In this paper, a novel RSA is proposed to discover classification rules through a process of knowledge induction which selects decision rules with hierarchical design features for process knowledge classification of real-valued data in process industry. A way is also presented to reduce decision tables and to induce decision rules from rough approximations. Numerical examples are employed to substantiate the conceptual arguments.