Discovery of Knowledge in Electrical Power systems

Abstract

This paper concerns the presentation phase of a knowledge discovery process with use of association rules. The employment of the association rules model, the major technique of data mining, to knowledge discovering from the data of energy consumption is presented. The Predictive Model Markup Language (PMML) and XQuery language are involved to facilitate an environment for the systematic examination of complex mining models. A genetic programming approach to reducing complex association rule models is also introduced in the final part of the paper.