Designing an Expert System for Analyzing the Energy Consumption Behavior of Employees in Organizations Using Rough Set Theory

Understanding and changing the energy consumption behavior requires extensive knowledge about the motives of behavior. In this research, Rough Set Theory is used to investigate the energy consumption behavior of employees in organizations. So, thirteen condition attributes and a decision attribute have been selected and the decision system has been created. Condition attributes include demographic, values, attitudes and organizational characteristics of employees and decision attribute relates to energy consumption behavior. 482 employees have been selected randomly from 37 office buildings of ministry of Petroleum and rough modeling has been performed for them. By combining different methods of discretizing, reduction algorithms and rule generating, nine models have been made using ROSETTA software. The results show that four of the 13 condition attributes, involving “organizational citizenship”, “satisfaction”, “attitude toward behavior” and “lighting control” have been selected as the main features of the system. After cross validation of the various models, the model of manually discretizing using genetic algorithms and ORR approach to extract reducts has been had the most accuracy and selected as the most reliable model.