All Issue

2021 Vol.15, Issue 2 Preview Page

Research Article

April 2021. pp. 152-165
Abstract
References
1
Kim, J.H., Seong, N.C., Choi, W.C., Choi, K.B. (2018). An Analysis of the Prediction Accuracy of HVAC Fan Energy Consumption According to Artificial Neural Network Variables. Journal of the Architectural Institute of Korea Structure & Construction, 34(11), 73-79.
2
Kim, K.S., Yoo, D.C., Choi, C.H., Jang, H.I. (2020). Development of Energy Variable Definition and Reference Model for Predicting Energy Consumption of Low-rise Residential Buildings. Journal of the Architectural Institute of Korea, 2020, 36, 199-208.
3
Nam, Y.G., Hong, S.K., Cho, S.H., Choi, C.Y. (2019). A Study on the Prediction of Building Energy Consumption Using Deep Learning Technique. Journal of the Korean Society of Mechanical Technology, 21(6), 136-1144.
4
Bae, J.G. (2019). Development of Energy Consumption Prediction Model using Economizer Method in the Office Building with Machine Learning. Master's thesis. Department of Architectural Engineering, Yonsei University, Korea.
5
Hong, S.W. (2020). Prediction for Building and Housing Energy Saving Using Weather Information and Machine Learning. Doctoral thesis, Department of Intelligent Robot Engineering, Hanyang University, Korea.
6
Jung, J.H. (2018). Electricity Load Forecasting with Weather Data for Commercial Buildings based on Machine Learning. Master's thesis. Department of Architectural Engineering, Cheongju University, Korea.
7
Lee, S.H. (2020). An Analysis and Prediction of Energy consumption in a building using life patterns of Single-Person Households. Master's thesis. Department of Architecture, Sejong University, Korea.
8
Lee, T. G. (2015). Study on Electric Power Consumption in The University Building using Multiple Regression Analysis and Energy Simulation. Master's thesis. Department of Mechanical Engineering, University of Seoul, Korea.
9
No, B.I. (2015). Prediction of Heating Energy Consumption of Apartment Buildings Using Performance Evaluation of Detailed Heating Degree-days. Master's thesis. Department of Architectural Engineering, Chungbuk National University, Korea.
10
Park, G.H. (2018). Machine learning for building energy management Based on short/long-term prediction algorithm Performance analysis. Master's thesis. Department of Computer and Information Science, Korea University, Korea.
11
Ministry of Land, Infrastructure and Transport (MOLIT). (2018). 2030 Greenhouse Gas Reduction Roadmap Amendment and 2018-2020 emission permit allocation plan confirmed : Ministry of Land, Infrastructure and Transport.
12
ASHARAE (2002). ASHRAE Guideline 14 Measurement of Energy, Demand and Water Savings. American Society of Heating, Refrigerating, and Air-Conditioning Engineers, New York, USA.
Information
  • Publisher :Korean Institute of Architectural Sustainable Environment and Building Systems
  • Publisher(Ko) :한국건축친환경설비학회
  • Journal Title :Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
  • Journal Title(Ko) :한국건축친환경설비학회 논문집
  • Volume : 15
  • No :2
  • Pages :152-165
  • Received Date :2020. 12. 30
  • Revised Date :2021. 02. 15
  • Accepted Date : 2021. 02. 17
Journal Informaiton Journal of Korean Institute of Architectural Sustainable Environment and Building Systems Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close