A decision support model for reducing electric energy consumption in elementary school facilities

Taehoon Hong, Choongwan Koo, Kwangbok Jeong

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)


The South Korean government has been actively promoting an educational-facility improvement program as part of its energy-saving efforts. This research seeks to develop a decision support model for selecting the facility expected to be effective in generating energy savings and making the facility improvement program more effective. In this research, project characteristics and electric-energy consumption data for the year 2009 were collected from 6282 elementary schools located in seven metropolitan cities in South Korea. In this research, the following were carried out: (i) a group of educational facilities was established based on electric-energy consumption, using a decision tree; (ii) a number of similar projects were retrieved from the same group of facilities, using case-based reasoning; and (iii) the accuracy of prediction was improved, using the combination of genetic algorithms, the artificial neural network, and multiple regression analysis. The results of this research can be useful for the following purposes: (i) preliminary research on the systematic and continuous management of educational facilities' electric-energy consumption; (ii) basic research on electric-energy consumption prediction based on the project characteristics; and (iii) practical research for selecting an optimum facility that can more effectively apply an educational-facility improvement program as a decision support model.

Original languageEnglish
Pages (from-to)253-266
Number of pages14
JournalApplied Energy
Publication statusPublished - 2012 Jul

Bibliographical note

Funding Information:
This research was supported by a grant from High-Tech Urban Development Program (10CHUD-C03) funded by the Ministry of Land, Transport and Maritime affairs, South Korea. This research was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Education, Science and Technology, MEST) (No. 2011-0018360).

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Energy(all)
  • Management, Monitoring, Policy and Law
  • Building and Construction
  • Renewable Energy, Sustainability and the Environment


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