Knowledge Discovery of Energy Management System Based on Prism, FURIA and J48

Facing mountains of data in modern energy management system, Related operators need to use machine learning to derive corresponding knowledge to support its decision-making. In view of the above question, Based on Prism, FURIA and the J48 classifier, this paper used 10 fold cross validation on the energy management system for training a data table TP rate respectively were: 92%, 88% and 84%, Prism classifier produced 5 rules, FURIA classifier produced 4 rules, decision tree generated by J48 had 5 valid braches ∘ Rules generated by classifiers can provide decision-making guidance for energy management system, and accelerate decision-making response performance.