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BROWSE대한건축학회 논문집(구조계)2018-11 > DETAIL
  LITERATURE >JOURNALS [380701] Download the full text :   
Title   인공신경망 변수에 따른 HVAC 에너지 소비량 예측 정확도 평가 / 송풍기를 중심으로 / An Analysis of the Prediction Accuracy of HVAC Fan Energy Consumption According to Artificial Neural Network Variables
Authors   김지헌(Kim, Jee-Heon) ; 성남철(Seong, Nam-Chul) ; 최원창(Choi, Won-Chang) ; 최기봉(Choi, Ki-Bong)
Organization   대한건축학회
Source   대한건축학회논문집 구조계, Vol.34 No.11(2018-11)
Page   Start Page(73) Total Page(7)
ISSN   1226-9107
Classification   재료 / 환경 및 설비 
Keywords   건물 에너지 ; 공기조화시스템 ; 인공신경망//Building Energy ; HVAC ; Artificial Neural Networks
Abstract2   In this study, for the prediction of energy consumption in the ventilator, one of the components of the air conditioning system, the predicted results were analyzed and accurate by the change in the number of neurons and inputs. The input variables of the prediction model for the energy volume of the fan were the supply air flow rate, the exhaust air flow rate, and the output value was the energy consumption of the fan. A predictive model has been developed to study with the Levenbarg-Marquardt algorithm through 8760 sets of one-minute resolution. Comparison of actual energy use and forecast results showed a margin of error of less than 1% in all cases and utilization time of less than 3% with very high predictability. MBE was distributed with a learning period of 1.7% to 2.95% and a service period of 2.26% to 4.48% respectively, and the distribution rate of ±10% indicated by ASHRAE Guidelines 14 was high.8
Location   대한건축학회