논문 국내 국제전문학술지(SCI급) 전이 학습 기반 고정된 레이어 수에 따른 건물 전력 소비량 예측 정확도 검증
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2020-12
- 저자명 진경일,안유선,이용준
- 학술지명 한국태양에너지학회 논문집
- 발행처명 한국태양에너지학회
- 발행국가 국내
- 논문언어 한국어
- 전체저자수 3
홈페이지논문 초록 (Abstract)
Owing to recent advances in data-driven technologies, prediction models can now be utilized in various fields such as energy consumption prediction. Among them, transfer learning, which enables prediction using data collected for a short term, is actively gaining ground. In the field of building energy, attention is focused on predicting the power consumption of buildings with the development of smart grids and micro-grids. The purpose of this study is to implement a machine learning (ML) method using the transfer learning algorithm that enables the prediction of energy consumption of the buildings using data collected for a short-term period. This study also validates the accuracy of the predicted energy consumption by adjusting the number of frozen layers based on the input parameters used in the ML method. A total of 5 layers were set, and the frozen layers were increased from 0 to 5. In addition, to validate the prediction rate of the transfer learning algorithm, only the existing ML model was used. As a result, when 0 through 3 layers were fixed, the accuracy criterion tended to be met. In contrast, when the 4-5 layers were reflected, the accuracy criterion was not met. It should also be noted that the model without using transfer learning showed poor accuracy.